U.S. patent number 11,439,671 [Application Number 17/324,898] was granted by the patent office on 2022-09-13 for therapeutic bacterial composition.
This patent grant is currently assigned to Microbiotica Limited. The grantee listed for this patent is Microbiotica Limited. Invention is credited to Ghaith Bakdash, Simon Harris, Dominika Klisko, Trevor Lawley, Amy Popple, Matthew Robinson, Michael Romanos, Kevin Vervier.
United States Patent |
11,439,671 |
Robinson , et al. |
September 13, 2022 |
Therapeutic bacterial composition
Abstract
The invention relates to bacterial compositions useful in the
treatment of cancer. In particular, the compositions can be used as
a co-therapy with an immune checkpoint therapy. The invention also
relates to methods for identifying a subject that will respond to
therapy with an immune checkpoint inhibitor comprising determining
the abundance of bacteria in a biological sample from said
subject.
Inventors: |
Robinson; Matthew (Cambridge,
GB), Lawley; Trevor (Cambridge, GB),
Romanos; Michael (Cambridge, GB), Vervier; Kevin
(Cambridge, GB), Harris; Simon (Cambridge,
GB), Bakdash; Ghaith (Cambridge, GB),
Popple; Amy (Cambridge, GB), Klisko; Dominika
(Cambridge, GB) |
Applicant: |
Name |
City |
State |
Country |
Type |
Microbiotica Limited |
Cambridge |
N/A |
GB |
|
|
Assignee: |
Microbiotica Limited
(Cambridge, GB)
|
Family
ID: |
1000006557622 |
Appl.
No.: |
17/324,898 |
Filed: |
May 19, 2021 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20210275602 A1 |
Sep 9, 2021 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61K
45/06 (20130101); C12N 15/113 (20130101); C07K
16/2818 (20130101); C07K 16/2827 (20130101); G01N
33/4833 (20130101); A61K 35/74 (20130101); G01N
2333/195 (20130101); G01N 2800/52 (20130101); C07K
2317/73 (20130101) |
Current International
Class: |
A61K
35/74 (20150101); C07K 16/28 (20060101); C12N
15/113 (20100101); G01N 33/483 (20060101); A61K
45/06 (20060101) |
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Primary Examiner: Minnifield; Nita M.
Attorney, Agent or Firm: Myers Bigel, P.A.
Claims
The invention claimed is:
1. A method for treating melanoma or non-small cell lung cancer in
a subject in need thereof, comprising administering to the subject
a composition comprising isolated bacteria selected from at least
two species wherein the bacteria from the first species comprise a
16S rDNA sequence having at least 98.7% sequence identity with a
nucleic acid sequence according to SEQ ID NO: 1, and the bacteria
from the second species comprise a 16S rDNA sequence having at
least 98.7% sequence identity with a nucleic acid sequence
according to SEQ ID NO: 2 wherein said subject is receiving, has
received or will receive therapy with an anti-PD-1 or anti-PD-L1
antibody, thereby treating the melanoma or non-small cell lung
cancer in the subject.
2. The method according to claim 1, wherein said composition
further comprises one or more bacteria comprising a 16S rDNA
sequence selected from SEQ ID NOs: 3 to 15 or a sequence having at
least 98.7% sequence identity thereto.
3. The method according to claim 1, wherein said composition
further comprises bacteria from 7 different bacterial species
wherein said bacteria comprise a 16S rDNA sequence selected from
SEQ ID NO: 3 to 15 or a sequence having at least 98.7% sequence
identity thereto.
4. The method according to claim 1, wherein said composition
further comprises bacteria from 4 different bacterial species
wherein said bacteria comprise a 16S rDNA sequence selected from
SEQ ID NO: 3 to 15 or a sequence having at least 98.7% sequence
identity thereto.
5. The method according to claim 1, wherein the subject has
melanoma.
6. The method according to claim 5, wherein the melanoma is
Harding-Passey melanoma, juvenile melanoma, lentigo maligna
melanoma, malignant melanoma, acral-lentiginous melanoma,
amelanotic melanoma, benign juvenile melanoma, Cloudman's melanoma,
S91 melanoma, nodular melanoma, subungual melanoma, cutaneous
melanoma, uveal/intraocular melanoma, superficial spreading
melanoma, or cutaneous or intraocular malignant melanoma.
7. The method according to claim 1, wherein the immune checkpoint
inhibitor is selected from nivolumab, pembrolizumab, cemiplimab,
avelumab, durvalumab, atezolizumab, spartalizumab camrelizumab
sintilimab, or tislelizumab.
8. The method according to claim 1, wherein the composition is
administered by oral administration or rectal administration.
9. The method according to claim 1, wherein the composition is in
the form of a capsule, tablet, gel or liquid.
10. The method according to claim 1, wherein the subject has
received prior anti-cancer therapy with an anti-PD-1 or anti-PD-L1
antibody.
11. The method according to claim 1, wherein the anti-PD-1 or
anti-PD-L1 antibody is administered before, after or at the same
time as the bacterial composition.
12. The method according to claim 1, wherein the composition
comprises live, attenuated or killed bacteria.
13. The method according to claim 1, wherein the composition is
lyophilised.
14. The method according to claim 1, wherein the composition does
not comprise bacterial spores.
15. The method according to claim 1, further comprising surgical,
radiation, and/or chemotherapeutic cancer intervention or
administration of an anti-cancer therapeutic.
16. The method according to claim 1, wherein the subject has been
determined to be a non-responder to the previous anti-cancer
treatment with an anti-PD-1 or anti-PD-L1 antibody.
17. The method according to claim 1, wherein the subject has been
determined to have a microbial profile in the gut microbiome with
an abundance of one or more bacteria comprising a 16S rDNA sequence
selected from SEQ ID NOs: 1 to 15 or a sequence having at least
98.7% sequence identity thereto at or below a reference value from
subjects that do not respond to therapy with an anti-PD-1 or
anti-PD-L1 antibody.
18. The method according to claim 1, wherein said composition
further comprises bacteria species comprising a 16S rDNA sequence
from each of SEQ ID NOs: 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14
and 15 or a sequence having at least 98.7% sequence identity
thereto.
19. The method according to claim 1, wherein said composition
further comprises bacteria species comprising a 16S rDNA sequence
from each of SEQ ID NOs: 3, 4, 5, 6, 7, 8 and 9 or a sequence
having at least 98.7% sequence identity thereto.
20. The method according to claim 1, wherein said composition
further comprises bacteria species comprising a 16S rDNA sequence
from each of SEQ ID NOs: 3, 6, 7, 8, 9, 11, 12, 13, 14 and 15 or a
sequence having at least 98.7% sequence identity thereto.
21. The method according to claim 1, wherein said composition
further comprises bacteria species comprising a 16S rDNA sequence
from each of SEQ ID NOs: 3, 6, 7, 8, 9, 11 and 14 or a sequence
having at least 98.7% sequence identity thereto.
22. The method according to claim 1, wherein said composition
further comprises bacteria species comprising a 16S rDNA sequence
from each of SEQ ID NOs: 7, 9, 13, 16, 18, 19 and 20 or a sequence
having at least 98.7% sequence identity thereto.
23. The method according to claim 1, wherein said composition
further comprises bacteria species comprising a 16S rDNA sequence
from each of SEQ ID NOs: 7, 9, 18 and 20 or a sequence having at
least 98.7% sequence identity thereto.
24. The method according to claim 1, wherein said composition
further comprises bacteria comprising a 16S rDNA sequence of SEQ ID
NO: 7 or a sequence having at least 98.7% sequence identity
thereto.
25. The method according to claim 1, wherein said composition
further comprises bacteria species comprising a 16S rDNA sequence
from each of SEQ ID NOs: 3, 5, 7, 10, 11, 12, 13 and 14 or a
sequence having at least 98.7% sequence identity thereto.
Description
STATEMENT REGARDING ELECTRONIC FILING OF A SEQUENCE LISTING
A Sequence Listing in ASCII text format, submitted under 37 C.F.R.
.sctn. 1.821, entitled 1553-10 Sequence_ST25.txt, 62,388 bytes in
size, generated on May 18, 2021 and filed via EFS-Web, is provided
in lieu of a paper copy. This Sequence Listing is hereby
incorporated herein by reference into the specification for its
disclosure.
INTRODUCTION
Immune suppression and evasion by malignant cancer cells is known
as one of the hallmarks of cancer. A number of co-inhibitory
receptors and their ligands, known as immune checkpoints,
contribute to this process. Immune checkpoint inhibitor cancer
immunotherapies have been transformational in cancer management in
that they can lead to long-term remission and they can be effective
across many cancers. Among these checkpoints are programmed cell
death 1 (PD-1), PD-L1 and CTLA-4. The introduction of PD-1
inhibitors into clinical practice has had a revolutionary effect on
cancer treatment, but consistent responses and favourable long-term
outcomes are only observed in a fraction of patients. The majority
of patients do not respond to therapy. The highest proportion is
for melanoma (reaching 40%), but it is much lower for the other
cancers. Moreover, a significant number of patients develop
immune-related adverse events and have to stop therapy.
Accordingly, there is a need for (a) biomarkers to predict response
to immune checkpoint inhibitors and (b) approaches to increase the
proportion of cancer patients that respond to therapy.
PD-1 (UniProt Accession No. 015116, GenBank Accession No. U6488)
protein is encoded by the PDCD1 gene and expressed as a 55 kDa type
I transmembrane protein (Agata 1996 Int Immunol 8(5):785-72). PD-1
is an immunoglobulin superfamily member (Ishkda 1992 EMBO
11(11):3887-95) and it is an inhibitory member of the extended
CD28/CTLA-4 family of T cell regulators. Other members of this
family include CD28, CTLA-4, ICOS and BTLA. PD-1 exists as a
monomer, lacking the unpaired cysteine residue characteristic of
other CD28 family members (Zhang 2004 Immunity 20:337-47). Its
cytoplasmic domain contains an immunoreceptor tyrosine-based
inhibitory motif (ITIM) and an immunoreceptor tyrosine-based switch
motif (ITSM) that are phosphorylated during signal transduction
(Riley 2009 Immunol Rev 229(1):114-25).
PD-1 is expressed on B cells, T cells, and monocytes (Agata 1996).
The role of PD-1 in maintaining immunologic self-tolerance was
demonstrated in PDCD1-/- mice, which develop autoimmune disorders
(Nishimura 1999 Immunity 11:141-51, Nishimura 2001 Science
291(5502):319-22). The PD-1 pathway therefore regulates antigen
responses, balancing autoimmunity and tolerance.
There are two ligands for PD-1 that mediate its regulatory
function. PD-L1 (B7-H1) is normally expressed on dendritic cells,
macrophages, resting B cells, bone marrow-derived mast cells and T
cells as well as non-hematopoietic cell lineages (reviewed in
Francisco 2010 Immunol Rev 236:219-42). PD-L2 (B7-DC) is largely
expressed on dendritic cells and macrophages (Tseng 2001 J Exp Med
193(7):839-45). Ligand expression is influenced by local mediators
and can be upregulated by inflammatory cytokines.
PD-1 is known as an immunoinhibitory protein that negatively
regulates TCR signals. The interaction between PD-1 and PD-L1 can
act as an immune checkpoint, which can lead to, e.g., a decrease in
tumour infiltrating lymphocytes, a decrease in T-cell receptor
mediated proliferation, and/or immune evasion by cancerous cells.
Immune suppression can be reversed by inhibiting the local
interaction of PD-1 with PD-L1 or PD-L2; the effect is additive
when the interaction of PD-1 with both PD-L1 and PD-L2 is
blocked.
The PD-1 pathway can be exploited in cancer or infection, whereby
tumours or viruses can evade effective immune recognition and T
cells demonstrate an `exhausted` phenotype.
Disruption of the PD-1:PD-L1 interaction enhances T cell activity.
Inhibitory anti-PD-1 monoclonal antibodies demonstrate blockade of
the interaction between PD-1 and its ligands (Wang 2014 Cancer
Immunol Res 2(9):846-56). T cell function in vitro can be enhanced
by PD-1 blockade, as demonstrated by improved proliferation and
cytokine responses in mixed lymphocyte reactions of T cells and
dendritic cells. Cytotoxic T Lymphocytes (CTLs) derived from
melanoma patients have also been shown to be enhanced by PD-1
blockade in vitro using the antibody nivolumab, and can become
resistant to suppression by regulatory T cells (Wang 2009 Int
Immunol 21(9):1065-1077). This antibody has been shown to be
efficacious in melanoma and in non-small-cell lung carcinoma
(NSCLC) patients. Another PD-1 blocking antibody, pembrolizumab,
demonstrates responses in NSCLC patients refractory to CTLA-4
blockade. Nivolumab and pembrolizumab both functionally block the
interaction of human PD-1 with its ligands.
The gut microbiome of cancer patients is a major driver of response
to immune checkpoint therapy.
Previous studies have analysed clinical datasets to identify gut
microbiota associated with treatment efficacy (Frankel Neoplasia
(2017) 19:848; Gopalakrishnan Science (2018) 359:97; Matson Science
(2018) 359:104; Routy Science (2018) 359:91). However, the major
challenge in the field has been that the microbiome signatures
identified in the independent studies are very different. The
published studies vary in response criteria and cancer indication,
but also factors that are known to impact microbiome analysis such
as sample collection, storage and processing and geographical
location. Therefore, it has been difficult to understand what the
true signature is amongst the inter-study noise.
Thus, there is a need to provide efficacious treatments of cancer
as well as biomarkers that are predictive for response to treatment
and the present invention is aimed at addressing this need.
SUMMARY OF THE INVENTION
The invention is based on the finding that the gut microbiome in
subjects that respond to treatment with an immune checkpoint
inhibitor is different to the gut microbiome in subjects that do
not respond to treatment with the immune checkpoint inhibitor, and
that the gut microbiome may therefore be employed either as a
diagnostic for immune checkpoint inhibitor treatment or as the
source of a therapy.
The invention is therefore aimed at a number of aspects, including,
but not limited to the following: A composition comprising certain
bacteria as defined herein which have been identified in patients
who respond to treatment with an immune checkpoint inhibitor and
which can be used as a treatment of disease, including treatment of
cancer, an infectious disease or use as a vaccine adjuvant; A
co-therapy comprising a composition having certain bacteria as
defined herein and an immune checkpoint inhibitor treatment and
Provision of certain bacteria as defined herein as a diagnostic for
immune checkpoint inhibitor treatment to identify patients that
benefit from immune checkpoint inhibitor treatment and also to
identify patients which may receive bacterial or other therapy,
e.g. before administration of the checkpoint inhibitor therapy.
These aspects as well as other related aspects of the invention and
embodiments are further described herein.
The inventors have identified a microbiome biomarker signature
associated with and highly predictive of response to treatment with
an immune checkpoint inhibitor. This is of great significance in
the field, providing the basis for the following: a predictive
biomarker for checkpoint inhibitor therapy; a live bacterial
therapeutic (LBT) therapy; a live bacterial therapeutic co-therapy
with an immune checkpoint inhibitor, for example anti-PD-1,
anti-PD-L1 or anti-CTLA-4 drugs for the treatment of cancer, to
increase the proportion of patients responding to checkpoint
inhibitors. In particular, the inventors have identified a number
of bacterial species present in the gut microbiome that exhibit
modulated abundance indicative of a response to treatment with an
immune checkpoint inhibitor. Detecting modulated abundance of these
bacteria may therefore be employed to discriminate responders to
checkpoint inhibitor therapy from non-responders. In addition, the
administration of such live bacteria as a medicine is predicted to
convert patients not responding to checkpoint inhibitors to
responders.
The bacteria identified and described herein may be employed
individually to determine response and/or provide treatment, or
combinations of the bacteria may be provided to increase the
discriminatory power of the diagnostic method and provide
non-invasive methods of diagnosis for response versus non-response
as well as methods of treatment.
The inventors have identified specific gut bacteria associated with
checkpoint inhibitor response. The invention thus provides gut
bacteria that can be used to modulate the microbiome to improve the
therapeutic response to immune checkpoint inhibitors patients, for
example cancer patients. Studies in the present disclosure used a
cohort of patients with melanoma undergoing therapy with anti-PD-1
drugs or combination therapy with anti-PD-1 plus anti-CTLA-4 drugs.
Gut microbiome samples taken prior to immune checkpoint therapy
were characterized in these patients via metagenomic whole genome
shotgun sequencing. Significant differences were observed in the
composition of the gut microbiome in responders versus
non-responders to immune checkpoint blockade therapy (e.g., to
PD-1-based therapy), with an increase or decrease in abundance of
specific bacteria in the gut microbiome of responders versus
non-responders pre-treatment. In particular, the bacteria as
described herein were found to be more abundant in responders.
Therefore, these bacteria and subsets thereof find use in a
composition which can be employed for the treatment of disease,
including cancer, either alone or in combination with an immune
checkpoint inhibitor treatment. Furthermore, these bacteria can be
used as biomarkers, i.e. as a diagnostic to distinguish responders
to checkpoint inhibitor, e.g. PD-1 inhibitor, therapy from
non-responders for immune checkpoint inhibitor treatment.
The present studies show that patients with a "favourable" gut
microbiome (with modulated, e.g. high relative abundance of one or
more of bacteria as described herein) have enhanced anti-tumour
immune responses. In contrast, patients with an "unfavourable" gut
microbiome (with low relative abundance of the species B1-B15 as
defined herein) have impaired anti-tumour immune responses. These
findings highlight the potential for parallel modulation of the gut
microbiome to significantly enhance checkpoint blockade treatment
efficacy. Based on these findings, methods of disease management,
e.g. cancer treatment and diagnosis are provided herein. Also
provided herein are methods to use the compositions described
herein as predictive biomarker compositions to identify patients
who will have a favourable response to immune checkpoint blockade.
Moreover, the compositions described herein have immunostimulatory
properties. Therefore, treatment of disease is not limited to
cancer, but the compositions provides treatment of other diseases,
e.g. diseases that benefit form immunostimulatory treatment, e.g.
non-cancer immunotherapies.
In a first aspect, the invention thus relates to a composition
comprising one or more bacterial isolate, in particular a bacterial
population, belonging to one or more bacterial species selected
from Table 1. Thus, the invention relates to a composition
comprising a bacterium selected from one or more bacteria selected
from Table 1. Specifically, the invention thus relates to a
composition comprising one or more bacterial isolate having a
16SrDNA selected from SEQ ID. Nos 1 to 15.
The composition may comprise or consists of 2, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12, 13, 14 or 15 isolated bacteria. These are different
bacteria selected from different species, that is bacteria having a
16SrDNA of selected from SEQ ID. Nos 1 to 29 or a sequence having
at least 95%, 97%, 98% 98.7%, 99% or 100% sequence identity with a
nucleic acid sequence selected from SEQ ID. Nos 1 to 29, e.g.
selected from SEQ ID. Nos 1 to 15 or a sequence having at least
95%, 97%, 98% 98.7% or 99% sequence identity with a nucleic acid
sequence selected from SEQ ID. Nos 1 to 15.
In one embodiment, the composition thus comprises or consists of
isolated bacteria selected from at least 2, 3, 4, 5, 6, 7, 5, 9,
10, 11, 12, 13, 14 or 15 bacterial species wherein the bacteria
comprise a 16S rDNA sequence selected from SEQ ID. Nos 1 to 29,
e.g. 1 to 15, or a sequence having at least 95%, 97%, 98% 98.7%,
99% or 100% sequence identity with a nucleic acid sequence selected
from SEQ ID. Nos 1 to 15.
In one embodiment, the composition comprises or consists of
isolated bacteria selected from at least two species wherein the
bacteria from the first species comprise a 16S rDNA sequence having
least 95%, 97%, 98%, 98.7%, 99% or 100% sequence identity with a
nucleic acid sequence according to SEQ ID NO: 1, and the bacteria
from the second species comprise a 16S rDNA sequence having at
least 95%, 97%, 98%, 98.7%, 99% or 100% sequence identity with a
nucleic acid sequence according to SEQ ID NO: 2.
In one embodiment, the composition comprises or consists of
isolated bacteria selected from at least 9 species wherein the
bacteria comprise a 16S rDNA sequence selected from SEQ ID. Nos 1
to 29, e.g. 1 to 15 or a sequence having at least 95%, 97%, 98%,
98.7%, 99% or 100% sequence identity with a sequence selected from
SEQ ID. Nos 1 to 29, e.g. 1 to 15. In one embodiment, the 9 species
include bacteria comprising a 16S rDNA sequence according to SEQ ID
NO: 1, or a sequence having at least 95%, 97%, 98% 98.7%, 99% or
100% sequence identity thereto and bacteria comprising a 16S rDNA
sequence according to SEQ ID NO: 2 or a sequence having at least
95%, 97%, 98%, 98.7%, 99% or 100% sequence identity thereto.
In another aspect, the invention relates to a pharmaceutical
composition as described herein, a pharmaceutical carrier and
optionally an immune checkpoint inhibitor.
In another aspect, the invention relates to a composition as
described herein for use in the treatment of disease, such as
particular cancer or an infectious disease. The composition can
also be used as a vaccine adjuvant. This is used to enhance vaccine
response and administration may be together with the vaccine.
In another aspect, the invention relates to a composition as
described herein in increasing efficacy of an anti-cancer treatment
with an immune checkpoint inhibitor.
In another aspect, the invention relates to a method for treating
cancer comprising modulating the level/abundance of one or more
bacteria selected from those of Table 1 in a subject.
In another aspect, the invention relates to a kit comprising a
composition as described herein and optionally an anti-cancer
treatment that includes an immune checkpoint inhibitor.
In another aspect, the invention relates to a method for
identifying a subject that will respond to therapy with an immune
checkpoint inhibitor comprising determining the abundance of one or
more bacteria selected from those of Table 1 in a biological sample
from said subject that comprises gut intestinal flora wherein an
increase in the abundance of one or more of bacteria selected from
those of Table 1 is indicative that the subject will respond to
therapy with an immune checkpoint inhibitor.
In another aspect, the invention relates to a use of a bacterium
selected from one or more bacteria selected from those of Table 1
in identifying a patient that win respond to therapy with an immune
checkpoint inhibitor.
In another aspect, the invention relates to a kit comprising; a
sealable container configured to receive a biological sample;
polynucleotide primers for amplifying a 16S rDNA polynucleotide
sequence from at least one gut associated bacterium to form an
amplified 16S rDNA polynucleotide sequence, wherein the amplified
16S rDNA sequence has at least 95%, 97%, 98%, 98.7%, 99% or 100%
sequence identity to a polynucleotide sequence selected from SEQ ID
NOs 1 to SEQ ID NO 29; e.g. 1 to 15, a detecting reagent to detect
the amplified 16S rDNA sequence; and instructions for use.
In another aspect, the invention relates to a food product or a
vaccine co-therapy to boost vaccine response comprising the
composition as described herein.
In another aspect, the invention relates to a method for
identifying a faecal donor, e.g. for treatment of cancer,
comprising assessing a faecal sample of a subject for the presence
of one or more bacteria selected from Table 1 and identifying the
faecal donor based on the presence and/or abundance of one or more
bacteria selected from Table 1.
In another aspect, the invention relates to a use of one or more
bacteria selected from Table 1 in a method for identifying a donor
for FMT therapy, e.g. for treatment of cancer.
In another aspect, the invention relates to a method for treating a
faecal transplant prior to administration to a subject comprising
supplementing the faecal transplant with one or more isolated
bacteria selected from Table 1.
In another aspect, the invention relates to a method for
screening/identifying a faecal donor comprising assessing a faecal
sample of a subject for the presence of one or more bacteria
associated with response to cancer; and identifying the faecal
donor based on the presence and/or abundance of one or more
bacteria.
DESCRIPTION OF FIGURES
FIG. 1. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of bacteria in a defined
signature. A cut off of 0.5 was used to determine the accuracy of
the prediction. Accuracy was 91.16%. x axis is group. B) As A
except each study is considered separately. frankel accuracy
84.62%; gajewski accuracy 89.74%; melresist accuracy 93.18%; wargo
accuracy 100%. X axis is group. C) Receiver Operating
Characteristic (ROC) curve of the combined melanoma dataset showing
False Positive Rate as a function of True Positive Rate based on
machine learning predictions based the same microbiome signature.
AUC=0.98. X axis is 1-specificity, y axis is sensitivity. D) As C
but each study is considered separately. Random forest out-of-bag
error was used to prevent overoptimistic performance and improve
generalizability. AUC frankel 0.958; AUC gajewski 0.978; AUC
melresist 0.983; AUC wargo 1. X axis is 1-specificity, y axis is
sensitivity.
FIG. 2. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of the 15 bacteria in
consortium 1. A cut off of 0.5 was used to determine the accuracy
of the prediction. Accuracy was 77.55%. B) As A except each study
is considered separately. frankel accuracy 79.49%; gajewski
accuracy 66.67%; melresist accuracy 81.82%; wargo accuracy 84%. C)
Receiver Operating Characteristic (ROC) curve of the combined
melanoma dataset showing False Positive Rate as a function of True
Positive Rate based on machine learning predictions based on
consortium 1. AUC=0.8. D) As C but each study is considered
separately. Random forest out-of-bag error was used to prevent
overoptimistic performance and improve generalizability. AUC
frankel 0.867; AUC gajewski 0.725; AUC melresist 0.879; AUC wargo
0.773.
FIG. 3. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of the 9 bacteria in consortium
2. A cut off of 0.5 was used to determine the accuracy of the
prediction. Accuracy was 74.15%. B) As A except each study is
considered separately. frankel accuracy 76.92%; gajewski accuracy
69.23%; melresist accuracy 75%; wargo accuracy 76%. C) Receiver
Operating Characteristic (ROC) curve of the combined melanoma
dataset showing False Positive Rate as a function of True Positive
Rate based on machine learning predictions based on consortium 2.
AUC=0.75. D) As C but each study is considered separately. Random
forest out-of-bag error was used to prevent overoptimistic
performance and improve generalizability. AUC frankel 0.831; AUC
gajewski 0.676; AUC melresist 0.788; AUC wargo 0.734.
FIG. 4. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of the 12 bacteria in
consortium 3. A cut off of 0.5 was used to determine the accuracy
of the prediction. Accuracy was 74.15%. B) As A except each study
is considered separately. frankel accuracy 76.92%; gajewski
accuracy 66.67%; melresist accuracy 81.82%; wargo accuracy 68%. C)
Receiver Operating Characteristic (ROC) curve of the combined
melanoma dataset showing False Positive Rate as a function of True
Positive Rate based on machine learning predictions based on
consortium 3. AUC=0.773. D) As C but each study is considered
separately. Random forest out-of-bag error was used to prevent
overoptimistic performance and improve generalizability. AUC
frankel 0.844; AUC gajewski 0.685; AUC melresist 0.862; AUC wargo
0.76.
FIG. 5. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of the 9 bacteria in consortium
4. A cut off of 0.5 was used to determine the accuracy of the
prediction. Accuracy was 71.43%. B) As A except each study is
considered separately. frankel accuracy 76.92%; gajewski accuracy
64.1%; meiresist accuracy 77.27%; wargo accuracy 64%. C) Receiver
Operating Characteristic (ROC) curve of the combined melanoma
dataset showing False Positive Rate as a function of True Positive
Rate based on machine learning predictions based on consortium 4.
AUC=0.737. D) As C but each study is considered separately. Random
forest out-of-bag error was used to prevent overoptimistic
performance and improve generalizability. AUC frankel 0.781; AUC
gajewski 0.667; AUC melresist 0.791; AUC wargo 0.708.
FIG. 6. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of the 9 bacteria in consortium
5. A cut off of 0.5 was used to determine the accuracy of the
prediction. Accuracy was 68.71%. B) As A except each study is
considered separately. frankel accuracy 71.79%; gajewski accuracy
58.97%; meiresist accuracy 70.45%; wargo accuracy 76%. C) Receiver
Operating Characteristic (ROC) curve of the combined melanoma
dataset showing False Positive Rate as a function of True Positive
Rate based on machine learning predictions based on consortium 3.
AUC=0.69. D) As C but each study is considered separately. Random
forest out-of-bag error was used to prevent overoptimistic
performance and improve generalizability. AUC frankel 0.75; AUC
gajewski 0.596; AUC melresist 0.766; AUC wargo 0.675.
FIG. 7. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of the 9 bacteria in consortium
6. A cut off of 0.5 was used to determine the accuracy of the
prediction. Accuracy was 69.39%. B) As A except each study is
considered separately. frankel accuracy 69.23%; gajewski accuracy
58.97%; melresist accuracy 77.27%; wargo accuracy 72%. C) Receiver
Operating Characteristic (ROC) curve of the combined melanoma
dataset showing False Positive Rate as a function of True Positive
Rate based on machine learning predictions based on consortium 3.
AUC=0.71. D) As C but each study is considered separately. Random
forest out-of-bag error was used to prevent overoptimistic
performance and improve generalizability. AUC frankel 0.767; AUC
gajewski 0.577; AUC melresist 0.81; AUC wargo 0.708.
FIG. 8. Receiver Operating Characteristic (ROC) curve of a NSCLC
cohort showing False Positive Rate as a function of True Positive
Rate based on machine learning predictions based on consortium 1.
NSCLC dataset is metagenomic sequence from Routy and Zitvogel et al
(2018 Science 359:91-97) classified using the Microbiotica
high-precision platform. Random forest out-of-bag error was used to
prevent overoptimistic performance and improve generalizability.
AUC=0.744.
FIG. 9. Isolated bacteria induce dendritic cell maturation and
cytokine production. The ability of the isolated bacteria to
activate dendritic cells (DCs) was determined by co-culturing with
human monocyte-derived Dendritic cells in anaerobic conditions at
multiplicity of infection (MOI) of approximately 10:1. Subsequent
maturation of the dendritic cells was determined by expression
levels of the maturation markers CD86 (A) and CD83 (B) as
determined by flow cytometry. Data is displayed as fold change of
mean fluorescence intensity (MFI), compared to the LPS control to
normalise across different donors and experiments. The DC
expression of CD86 (C) and CD83 (D) following treatment with
consortium 5 (MOI of approximately 10:1) was similarly determined
by flow cytometry. The MFIs of those markers following stimulation
with consortium 5 are displayed in white bars. The DC expression of
CD86 (E) and CD83 (F) following treatment with consortia 6, 7, 8
and 9 was determined by flow cytometry. The MFIs of those markers
are displayed in white bars. (G) IL-12 and IL-10 production by DCs
following treatment with isolated bacteria alone (MOI of
approximately 10:1) or as consortia 5 and 6 (MOI of approximately
10:1) were determined by ELISA. MOI 10 N=5 (5 donors in 5
independent experiments). Data are displayed as ratio of IL-12 to
IL-10. LPS (10 ng/ml), Poly I:C (20 .mu.g/ml) and Salmonella
typhimurium (MOI of approximately 10:1) are strong inducers of DC
activation and used as positive controls for all assays (grey
bars). Unstimulated or immature (Imm) DCs are shown for comparison
(grey bars). Results are the mean.+-.SEM of 5 (A and B), 2 (C, D, E
and F) and 3 (G) independent experiments.
FIG. 10. Dendritic cells treated with isolated bacteria activate
Cytotoxic CD8+ T Lymphocytes (CTLs). Following co-culture with
isolated bacteria or control stimuli as in FIG. 9, human
monocyte-derived DCs were washed and co-cultured with purified
allogenic CD8+ T cells for 6 days. CTL activation was determined by
analysing the expression of Granzyme B (A). IFN-.gamma. (B) and
Perforin (C) using intracellular staining and flow cytometry. Data
is displayed as fold change of the percentage of positive cells,
compared to the LPS control to normalise across different donors
and experiments. LPS (10 ng/ml), Poly I:C (20 .mu.g/ml) and
Salmonella typhimurium (MOI of approximately 10:1) are strong
inducers of DC activation and used as positive controls for all
assays (grey bars). Unstimulated or immature (Imm) DCs are shown
for comparison (grey bars). Results are the mean.+-.SEM of 7 donors
in 4 independent experiments.
FIG. 11. Dendritic cells treated with consortia 6, 7, 8 and 9
activate Cytotoxic CD8+ T Lymphocytes (CTLs). Following co-culture
with consortia 6, 7, 8 and 9 or control stimuli as in FIG. 9, human
monocyte-derived DCs were washed and co-cultured with purified
allogenic CD8+ T cells for 6 days. CTL activation was determined by
analysing the expression of Granzyme B (A), IFN-.gamma. (B) and
Perforin (C) using intracellular staining and flow cytometry. Data
is displayed as the percentage of positive cells. LPS (10 ng/ml),
Poly I:C (20 .mu.g/ml) and Salmonella typhimurium (MOI of
approximately 10:1) are strong inducers of DC activation and used
as positive controls for all assays (grey bars). Unstimulated or
immature (Imm) DCs are shown for comparison (grey bars). Results
are the mean.+-.SEM of a duplicate of a single representative
experiment.
FIG. 12. Dendritic cells treated with consortium 5 activate
Cytotoxic CD8+ T Lymphocytes (CTLs). Following co-culture with
consortium 5 or control stimuli as in FIG. 11, human
monocyte-derived DCs were washed and co-cultured with purified
allogenic CD8+ T cells for 6 days. CTL activation was determined by
analysing the expression of Granzyme B (A), IFN-.gamma. (B) and
Perforin (C) using intracellular staining and flow cytometry. Data
is displayed as the percentage of positive cells. LPS (10 ng/ml),
Poly I:C (20 .mu.g/ml) and Salmonella typhimurium (MOI of
approximately 10:1) are strong inducers of DC activation and used
as positive controls for all assays (grey bars). Unstimulated or
immature (Imm) DCs are shown for comparison (grey bars). Results
are the mean.+-.SEM of a duplicate of a single representative
experiment.
FIG. 13. Isolated bacteria and consortia 6, 7, 8 and 9 endow the
induced CTLs with tumor killing capacity. CD8+ T cells primed by
bacteria/consortia-treated DCs (as in FIGS. 10 and 11) were
assessed for their capacity to kill SKOV-3 cells. Cytolysis is
determined by measuring the decreasing electric impedance of the
SKOV-3 cells. Data is displayed as the percentage of cytolysis of
SKOV-3 cells, 72 hours following co-culture with CD8+ T cells. LPS
(10 ng/ml), Poly I:C (20 .mu.g/ml) and Salmonella typhimurium (MOI
of approximately 10:1) are strong inducers of DC activation and
used as positive controls for all assays (grey bars). Unstimulated
or immature (Imm) DCs are shown for comparison (grey bars). Results
are the mean.+-.SEM of 3 independent experiments.
FIG. 14. Consortium 5 and Blautia sp. endow the induced CTLs with
tumor killing capacity. CD8+ T cells primed by consortium 5- or
Blautia sp.-treated DCs (as in FIG. 12) were assessed for their
capacity to kill SKOV-3 cells. Cytolysis is determined by measuring
the decreasing electric impedance of the SKOV-3 cells. Data is
displayed as the percentage of cytolysis of SKOV-3 cells, 72 hours
following co-culture with CD8+ T cells. LPS (10 ng/ml), Poly I:C
(20 .mu.g/ml) and Salmonella typhimurium (MOI of approximately
10:1) are strong inducers of DC activation and used as positive
controls for all assays (grey bars). Unstimulated or immature (Imm)
DCs are shown for comparison (grey bars). Results are the
mean.+-.SEM of a duplicate of a single representative
experiment.
FIG. 15. Isolated bacteria possess a variable capacity to induce
IFN-.alpha. production by plasmacytoid dendritic cells. IFN-.alpha.
production by plasmacytoid dendritic cells (pDCs) was determined by
ELISA following an overnight incubation with heat-killed bacteria
(moimoi of approximately 10:1). 10 ng/ml IL-3 and 10 .mu.g/ml CpG
(grey bars) were taken along as a negative and positive controls,
respectively. Results are the mean.+-.SEM of 3 donors in 2
independent experiments.
FIG. 16. In vivo efficacy in a murine cancer model Prior to tumour
implantation, SPF C57BL/8N female mice were administered
antibiotics in drinking water (kanamycin (0.4 mg/ml), colistin (850
U/ml), metronidazole (0.215 mg/m), vancomycin (0.045 mg/ml),
gentamycin (0.035 mg/ml)) for 7 days (day -9 to day -2).
Subsequently, mice were reconstituted with human donor stool from a
melanoma patient (20 mg) by oral gavage on day -1. 5.times.10.sup.5
MCA-205 murine fibrosarcoma cells were implanted subcutaneously in
the flank on day 0. Consortium 5 (n=8) and consortium 6 (n=8) were
administered by oral gavage twice weekly from day -1 for 3 weeks
(approximate total of 1.times.10.sup.9 CFU/dose) and compared to
animals treated with vehicle controls. Anti-PD-1 antibody (RMP1-14)
was administered (10 mg/kg intraperitoneal) thrice weekly for 2
weeks from day 6. Plots show tumour growth, as measured by volume,
over time in response to vehicle control, anti-PD1 and Consortium 5
(A) or consortium 6 (B). Data are mean.+-.SEM tumour size, and
representatives of at least three (A) and two (B) experiments.
FIG. 17. A) All 147 patients from the four melanoma studies were
divided into responders and non-responders according to clinical
outcome. The probability of not responding to immunotherapy was
predicted from the baseline faecal sample based on machine learning
predictions that used the abundance of the 9 bacteria in consortium
10. A cut off of 0.5 was used to determine the accuracy of the
prediction. Accuracy was 75.51%. B) As A except each study is
considered separately. frankel accuracy 74.38%; gajewski accuracy
71.79%; melresist accuracy 77.27%; wargo accuracy. C) Receiver
Operating Characteristic (ROC) curve of the combined melanoma
dataset showing False Positive Rate as a function of True Positive
Rate based on machine learning predictions based on consortium 3.
AUC=0.81. D) As C but each study is considered separately. Random
forest out-of-bag error was used to prevent overoptimistic
performance and improve generalizability. AUC frankel 0.85; AUC
gajewski 0.725; AUC melresist 0.826; AUC wargo 0.805.
In the figures, Con stands for consortium. Consortia are shown in
Table 3.
DETAILED DESCRIPTION
The present invention will now be further described. In the
following passages, different aspects of the invention are defined
in more detail. Each aspect so defined may be combined with any
other aspect or aspects unless clearly indicated to the contrary.
In particular, any feature indicated as being preferred or
advantageous may be combined with any other feature or features
indicated as being preferred or advantageous.
Generally, nomenclatures used in connection with, and techniques of
microbiology, cell and tissue culture, pathology, molecular
biology, immunooncology, genetics and protein and nucleic acid
chemistry and hybridization described herein are those well-known
and commonly used in the art. The methods and techniques of the
present disclosure are generally performed according to
conventional methods well-known in the art and as described in
various general and more specific references that are cited and
discussed throughout the present specification unless otherwise
indicated. See, e.g., Green and Sambrook et al., Molecular Cloning:
A Laboratory Manual, 4th ed., Cold Spring Harbor Laboratory Press,
Cold Spring Harbor, N.Y. (2012).
The nomenclatures used in connection with, and the laboratory
procedures and techniques of analytical chemistry, microbiology,
bioinformatics and medicinal and pharmaceutical chemistry described
herein are those well-known and commonly used in the art.
The invention relates to bacterial compositions each comprising or
consisting of one or more bacterial isolate from one or more
species as disclosed herein, e.g., a consortium of defined
bacterial isolates. The compositions have immunostimulatory
properties and are thus therapeutic compositions useful in the
treatment of disease. In some embodiments, the compositions are
mixtures of bacterial isolates selected from more than one species
as identified in Table 1.
The compositions are not faecal microbiota transplants (FMT) and do
not contain faecal material, but contain defined mixtures of
bacterial isolates free of faecal material. Therefore, preparations
that contain a defined bacterial mixture are generally accepted to
be a safer treatment than FMT. An advantage of the present
composition is that it comprises only fully defined and
characterised bacteria and no undefined or unwanted components,
which may be present in donor stools, thereby allowing the
therapeutic composition to be standardised and increasing safety of
the composition.
FMT relies on a stool sample from a human donor which is
administered directly to the recipient, e.g. via colonoscopy,
without bacteria present in the stool sample being isolated prior
to the administration of the FMT to the recipient. While FMT is
widely used, there are some disadvantages associated with FMT. The
composition of the FMT material is very donor dependent and
therefore is inconsistent. Despite screening of donors, it is
difficult to determine the bacterial load of the samples. Donors
also have to be screened for pathogens and to assess the risk of
colonization with drug-resistant bacteria. In certain aspects
described below, the invention also relates to augmenting FMT
therapy with one or more bacterial isolate from one or more species
as disclosed herein and methods for screening/identifying a faecal
donor.
The compositions as described herein include isolated bacteria. The
term "isolated" refers to bacteria that are isolated from the
natural environment. The isolated bacteria, e.g. isolated bacterial
strains, are substantially free of other cellular material,
chemicals and/or faecal material. Thus, as used herein, the term
"isolated" bacteria refers to bacteria that have been separated
from one or more undesired component, such as another bacterium or
bacterial strain, one or more component of a growth medium, and/or
one or more component of a sample, such as a faecal sample. In some
embodiments, the bacteria are substantially isolated from a source
such that other components of the source are not detected. As used
herein, the term "species" refers to a taxonomic entity as
conventionally defined by genomic sequence and/or phenotypic
characteristics. A "strain" is a particular instance of a species
that has been isolated and purified according to conventional
microbiological techniques. It will be understood that the terms
bacteria and bacterial isolates refer to a plurality of bacteria,
that is a bacterial population.
In one embodiment, the bacteria of the composition are
metabolically inactive prior to administration. For example, the
bacteria are lyophilsed. In one embodiment, the composition
includes vegetative bacterial cells and does not include bacterial
spores. In one embodiment, the composition includes vegetative
bacterial cells and/or bacterial spores. In one embodiment, the
composition includes vegetative bacterial cells and does not
include bacterial spores or is substantially devoid of spores. In
one embodiment, the composition includes fewer than about 0.5%, 1%,
2%, 3%, 4% or 5% spores.
The composition is preferably a live bacterial therapeutic,
bacteriotherapy or a live biotherapeutic product. As described
herein, a live bacterial product (also referred to as a bacterial
composition, live bacterial consortium, mixture of bacteria or
bacterial consortium) comprises one or more bacterial strain from
one or more bacterial species as described herein. The term live
bacterial therapy is interchangeably used with bacteriotherapy
herein and defines a therapy using live bacteria to restore health
or alleviate disease/disease symptoms or increase response to a
therapy.
The bacterial compositions of the invention provide an
immunostimulatory effect. In some embodiments, the bacterial
composition induces or stimulates an immunotherapeutic effect, for
example an anti-cancer effect (e.g., inhibition or cytotoxicity of
cancer cells), when administered to the subject. In some
embodiments, the bacterial composition induces or stimulates an
immune response that provides an anti-cancer or other beneficial
therapeutic effect when administered to the subject as further
explained herein.
As described herein, the composition may comprise one or more
bacterial species selected from those listed in Table 1. The
ability of the specific bacteria or the combination of bacterial
species of the live bacterial product to induce a beneficial
effect, i.e. an immunostimulatory effect, such as an anti-cancer
effect, can be assessed using any of method known in the art, e.g.,
in vitro assays for example using cell culture, or in vivo studies.
Suitable assays are shown in the examples.
In some embodiments, the anticancer live bacterial product induces
a specific immune cell population (e.g., CD8+ T-cells, Th17, Th1
cells). The abundance of a specific population of cells (e.g., CD8+
T-cells, Th17, Th1 cells) can be assessed by any method known in
the art, for example by detecting a cellular marker indicative of
the cell type, assessing a direct or indirect activity of the cell
type, and/or by measuring the production of one or more cytokines
produced by the specific cell type. In some embodiments, the
anti-cancer live bacterial product induces CD8+ T-cells (or "CD8+ T
cells"). As will be appreciated by one of ordinary skill in the
art, a combination of bacterial species and/or multiple strains
from one or more species as described herein may be selected and
combined to produce an anti-cancer live bacterial product that
induces CD8+ T-cells.
In one embodiment, the isolated bacteria, e.g. isolated bacterial
strains from the species listed herein, can be viable bacteria that
are capable of colonising the gastrointestinal gut of a subject
when administered to said subject.
The inventors have shown that by combining bacteria from different
species, a therapeutic composition can be provided which finds use
as a co-therapy with a checkpoint inhibitor. In a first aspect, the
invention relates to a composition comprising isolated bacteria,
e.g. a bacterial strain, selected from one or more of the bacterial
species B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14
and/or B15 as shown in Table 1 or subsets thereof. The invention
thus relates to a composition comprising one or more bacterial
isolate, e.g. bacterial population, having a 16SrDNA selected from
SEQ ID. Nos 1 to 19, e.g. 1 to 15. The invention thus relates to a
composition comprising or consisting of bacterial isolates of one
or more of the species as shown in Table 1.
Table 1 below lists the 15 different bacterial species from which
the isolated bacteria present in the composition are selected.
Reference to exemplary 16S rDNA sequence characterising each
species is also provided in Table 1. The terms 168S rDNA sequence
or 16S rDNA as used herein refer to DNA nucleic acid sequences,
i.e. a nucleic acid molecule, which encodes 16S rRNA nucleic acid
sequence i.e. a nucleic acid molecule. Nucleic acid sequences
referenced below are listed in Table 2. Also, as explained further
below, the bacteria of the composition and of other aspects as
described herein may have a 16S rDNA sequence with certain sequence
identity to the SEQ ID Nos. as listed below.
TABLE-US-00001 TABLE 1 Bacterial species of the composition and
biomarker signature 16S rDNA Possible alternative taxonomy:
sequence - name and/or closely related species sequence based on
closely related bacteria No Taxonomy identifier identified from
public databases B1 Eisenbergiella sp. SEQ ID No. 1; Eisenbergiella
tayi SEQ ID No. 21 B2 Butyricicoccus sp. SEQ ID No. 2;
Butyricicoccus pullicaecorum, SEQ ID No. 17; bacterium NLAE-zl-H41,
bacterium SEQ ID No. 22 NLAE-zl-H55, bacterium NLAE-zl-H60 B3
Clostridiales sp. SEQ ID No. 3 n/a B4 Alistipes obesi SEQ ID No. 4;
n/a SEQ ID No. 16 B5 Alistipes indistinctus SEQ ID No. 5 n/a B6
Gordonibacter SEQ ID No. 6; n/a urolithinfaciens SEQ ID No. 18; SEQ
ID No. 23 B7 Faecalitalea sp. SEQ ID No. 7; Longicatena caecimuris
SEQ ID No. 24 B8 Blautia sp. SEQ ID No. 8; Blautia products,
Blautia coccoides, SEQ ID No. 25 Blautia marasmi, Blautia stercoris
B9 Barnesiella SEQ ID No. 9; n/a intestinihorninis SEQ ID No. 26
B10 Alistipes timonensis SEQ ID No. 10 n/a B11 Blautia sp. SEQ ID
No. 11; n/a SEQ ID No. 19; SEQ ID No. 27 B12 Lachnospira sp. SEQ ID
No. 12; Lactobacillus rogosae SEQ ID No. 20; SEQ ID No. 28 B13
Ruminococcus callidus SEQ ID No. 13 n/a B14 Roseburia faecis SEQ ID
No. 14; n/a SEQ ID No. 29 B15 Faecalibacterium SEQ ID No. 15 n/a
prausnitzii
The aspects and embodiments of the invention described herein are
defined by reference to the species name and/or SEQ ID NO. as shown
in Table 1. In some cases, different exemplary sequences are
provided in Table 1 for the same species, e.g. corresponding to
different exemplary strains which belong to the same species. Where
multiple sequences are provided for a species, these sequences
share a high sequence identity, e.g. the different strains defined
by SEQ ID No. 2 and SEQ ID No. 17 have at least 99% sequence
identity, SEQ ID No. 4 and SEQ ID No. 16 have at least 99% sequence
identity. SEQ ID No. 6 and SEQ ID No. 18 have at least 99% sequence
identity and SEQ ID No. 12 and SEQ ID No. 20 have at least 99%
sequence identity.
In the aspects and embodiments described herein, for each of B1 to
B15, any of the sequences defined above (SEQ ID. Nos 1 to 29) can
be used. Thus, where multiple sequences are provided for a single
species, any of these sequences can be used.
It will be appreciated that the inventors provide compositions with
certain bacterial species that have immunostimulatory effects, e.g.
anti-cancer effects. It will also be appreciated that for each
species, different strains can be used, i.e. strains identified
above or other strains that belong to the same species. It should
be appreciated that closely related bacterial strains (e.g., as
defined by 16S rDNA sequences) having similar or the same
biological properties can also be included. In some embodiments,
bacterial strains provided herein can be replaced with bacterial
strains with similar or the same biological properties.
In some embodiments, the anticancer/live bacterial composition
comprises one or more bacterial strain of one or more of the 15
recited species shown in Table 1. In some embodiments, the
anticancer/live bacterial composition comprises one or more
bacterial strain of more than one of the 15 recited species; e.g.
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 species.
In one embodiment, the composition comprises or consists of 15
isolated bacteria. e.g. bacteria from each of the 15 bacterial
species listed in Table 1, for example with reference to the 18S
rDNA sequences as shown in the Table or a sequence with certain
percentage identity thereto as explained below or with reference to
the species name as shown above.
The invention also relates to compositions that comprise or consist
of bacteria selected from a subset of the bacterial species listed
in Table 1; e.g. compositions that comprise or consist of different
bacteria selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
14 or 15 of the bacterial species listed in Table 1, with reference
to the 16S rDNA sequences as shown in the Table 1 or a sequence
with certain percentage identity thereto as explained below or with
reference to the species name as shown above. All combinations are
envisaged.
Thus, in one embodiment, the composition comprises or consists of
at least one isolated bacterial population belonging to one or more
of the species in Table 1. For example, the composition comprises
or consists of bacteria selected from 2, 3, 6, 9 or 12 bacterial
species listed in Table 1. These may be selected from the consortia
shown in Table 3, for example consortia 2, 4, 5, 6 and 10. The
bacteria may be defined by reference to their 16S rDNA as shown in
the sequence identifiers Table 1. Thus, different bacteria selected
from those listed in Table 1 can be combined in a single
composition.
For example, the composition comprises or consists of isolated
bacteria selected from at least 2, e.g. up to 3, up to 4, up to 5,
up to 6, up to 7, up to 8, up to 9, up to 10, up to 11, up to 12,
up to 13, up to 14 or up to 15 species shown in Table 1, for
example with reference to the sequences as shown in the Table. For
example, the composition comprises or consists of isolated bacteria
from 9 bacterial species listed in Table 1. In one example, the
composition comprises or consists of isolated bacteria from 9
species as shown in Table 3, i.e. consortia 2, 4, 5, 6 and 10. The
bacteria may be defined by reference to their 16S rDNA as shown in
the sequence identifiers in Table 1.
In one embodiment, the composition comprises or consists of
isolated bacteria selected from 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14 or 15 species listed in Table 1, for example with reference
to the sequence IDs as shown in Table 1. In one embodiment, the
composition comprises or consists of isolated bacteria selected
from the consortia in Table 3. In one embodiment, the composition
comprises or consists of isolated bacteria having a 16S rDNA
selected from the SEQ ID NOs. as shown in Table 1. The bacteria may
be defined by reference to their 16S rDNA as shown in the sequence
identifiers in Table 1. Sequences with certain percentage sequence
identify as shown herein are also within the scope of the
invention.
In one embodiment, the composition comprises isolated bacteria
selected from at least 2, at least 3, at least 4, at least 5, at
least 6, at least 7, at least 8, at least 9, at least 10, at least
11, at least 12, at least 13, at least 14 or at least 15 species
listed in table 1, for example with reference to the sequences as
shown in table 1, for example with reference to the sequence IDs as
shown in Table 1. In one embodiment, the composition comprises
isolated bacteria selected from at least 9 species as shown in
Table 1. Sequences with certain percentage sequence identify as
shown herein are also within the scope of the invention.
In one embodiment, the composition comprises or consists of
isolated bacteria selected from no more than 2, no more than 3, no
more than 4, no more than 5, no more than 6, no more than 7, no
more than 8, no more than 9, no more than 10, no more than 11, no
more than 12, no more than 13, no more than 14 or no more than 15
species listed in Table 1, for example with reference to the
sequences as shown in table 1, for example with reference to the
sequence IDs as shown in Table 1. Sequences with certain percentage
sequence identify as shown herein are also within the scope of the
invention.
In one embodiment, the composition comprises or consists of
isolated bacteria selected from 2 to 4, 2 to 5, 2 to 6, 2 to 7, 2
to 8, 2 to 9, 2 to 10, 2 to 11, 2 to 12, 2 to 13, 2 to 14 or 2 to
15 species shown in table 1, for example with reference to the
sequences as shown in Table 1, for example with reference to the
sequence IDs as shown in Table 1. Sequences with certain percentage
sequence identify as shown herein are also within the scope of the
invention.
In one embodiment, the composition comprises an isolated bacterial
mixture comprising or consisting of 2 to 15 bacterial strains
having at least 90%, 95%, 97%, 98%, 98.7% or 99% sequence identity
to 16s rDNA sequences selected from SEQ ID Nos 1 to 15, e.g. SEQ ID
Nos. 16 to 29. Exemplary compositions are set out herein, e.g. In
Table 3.
A skilled person would appreciate that that bacterial species
selected from Table 1 and for use in the composition and methods of
the invention can have the sequence shown in Tables 1 and 2 or a
sequence that has certain percentage identity thereto and retains
biological activity; i.e. activity against cancer/efficacy in
enhancing the effect of a therapy using an immune checkpoint
inhibitor.
In one embodiment, the composition may be as described above, but
does not comprise bacteria of any other species, i.e. species not
listed in Table 1 or the composition comprise only de minimis or
biologically irrelevant amounts of bacteria from another species.
By biologically irrelevant is meant bacteria that do not have an
effect on the treatment of cancer. Thus, in one embodiment, the
composition consists of the recited bacteria.
In one embodiment, the composition does not comprise other
bacterial species that fall within a genus listed in Table 1.
In one embodiment, the composition may comprise other bacterial
species that fall within a genus listed in Table 1, but does not
comprise bacterial species of a genus not listed in Table 1. In one
embodiment, the composition may comprise other bacterial species
that fall within a different genus.
Methods of determining sequence identity are known in the art. It
is known that clades, operational taxonomic units (OTUs), species,
and strains are, in some embodiments, identified by their 16S rDNA
sequence. The relatedness can be determined by the percent identity
and this can be determined using methods known in the art.
Bacterial species and strains used in a composition as described
herein can be identified based on the 16S nucleic acid sequence
(full length or part thereof, such as V regions). The 168S
ribosomal DNA gene codes for the DNA component of the 30S subunit
of the bacterial ribosome. It is widely present in all bacterial
species. Different bacterial species have one to multiple copies of
the 16S rRNA gene. 16S rRNA gene sequencing is by far one of the
most common methods targeting housekeeping genes to study bacterial
phylogeny and genus/species classification. Thus, bacteria can be
taxonomically classified based on the sequence of the gene encoding
the 16S nucleic acid sequence, e.g. ribosomal DNA (rDNA) in the
bacterium. This gene sequence is also referred to as the ribosomal
DNA sequence (rDNA). The bacterial 16S rDNA is approximately 1500
nucleotides in length and is used in reconstructing the
evolutionary relationships and sequence similarity of one bacterial
isolate to another using phylogenetic approaches. 16S rDNA
sequences are used for phylogenetic reconstruction as they are in
general highly conserved, but contain specific hypervariable
regions that harbor sufficient nucleotide diversity to
differentiate genera and species of most microbes.
Using well known techniques to determine a full 16S rDNA sequence
or the sequence of any hypervariable region of the 16S rDNA
sequence, genomic DNA is extracted from a bacterial sample, the 16S
rDNA (full region or specific hypervariable regions) amplified
using polymerase chain reaction (PCR), the PCR products cleaned,
and nucleotide sequences delineated to determine the genetic
composition of the 16S rDNA gene or subdomain of the gene. If full
16S rDNA sequencing is performed, the sequencing method used may
be, but is not limited to, Sanger sequencing. If one or more
hypervariable regions are used, such as the V4 region, the
sequencing may be, but is not limited to being, performed using the
Sanger method or using a next-generation sequencing method, such as
an Illumina (sequencing by synthesis) method using barcoded primers
allowing for multiplex reactions. The V1-V9 regions of the 16S rDNA
refer to the first nine hypervariable regions of the 16S rDNA gene
that are often used for genetic typing of bacterial samples. In
some embodiments, at least one of V1 to V9 is used to characterise
the bacterial isolate.
In some embodiments, bacterial species identified as described
herein are identified by sequence identity to 16S rDNA sequences as
known in the art and described herein. In some embodiments, the
selected species are identified by sequence identity to full length
16S rDNA sequences as shown in Table 2. In some embodiments, the
selected species are identified by sequence identity to a part of
the 16S rDNA sequences as shown in Table 2, for example V3 and/or
V4.
As used herein, the term "homology" or "identity" generally refers
to the percentage of nucleic acid residues in a sequence that are
identical with the residues of the reference sequence with which it
is compared, after aligning the sequences and in some embodiments
after introducing gaps, if necessary, to achieve the maximum
percentage homology, and not considering any conservative
substitutions as part of the sequence identity. Thus, the
percentage homology between two nucleic acid sequences is
equivalent to the percentage identity between the two sequences.
Methods and computer programs for the alignment are well known. The
percentage identity between two sequences can be determined using
well known mathematical algorithms.
In one embodiment, the degree of sequence identity between a query
sequence and a reference sequence can be determined with the aid of
a commercially available sequence comparison program. This
typically involves aligning the two sequences using the default
scoring matrix and default gap penalty, identifying the number of
exact matches, and dividing the number of exact matches with the
length of the reference sequence. Suitable computer programs useful
for determining identity include, for example, BLAST
(blast.ncbi.nlm.nih.gov).
In the various embodiments as set out herein when reference is made
to a SEQ ID NO., sequences that have certain percentage sequence
identity to the full length sequence are also within the scope of
the invention.
Thus, the full length or partial 16S rDNA of the bacterial species
listed in Table 2 with reference to the sequence identifier in
Table 1 and which is used in the compositions and methods of the
invention has at least 90%, e.g. at least 91%, 92%, 93%, 94%, 95%,
96%, 97%, 98%, 98.7%, 99%, 99.5% or 100% sequence identity to the
corresponding reference 16S rDNA (i.e. SEQ IDs 1 to 29). In some
embodiments, the threshold sequence identity is at least 94.5%. In
one embodiment, said sequence identity is at least 95%. In one
embodiment, said sequence identity is at least 96%. In one
embodiment, said sequence identity is at least 97%. In one
embodiment, said sequence identity is at least 98%. In one
embodiment, said sequence identity is at least 98.7%. In one
embodiment, said sequence identity is at least 99%.
In one aspect, the composition therefore comprises two or more
bacteria, that is bacterial species, comprising a 16S rDNA sequence
selected from SEQ ID NO. 1 to 15 or comprising a 16S rDNA sequence
having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,
97%, 98%, 99%; e.g. 97% or 98.7% identity to a nucleic acid
sequence selected from SEQ ID NOs. 1 to 15. Such sequences include
SEQ ID. Nos 16 to 29, for example SEQ ID. Nos 16 to 20.
In some embodiments, the threshold sequence identity is 94.5%,
94.6%, 94.7%, 94.8%, 94.9%, 95.0%, 95.1%, 95.2%, 95.3%, 95.4%,
95.5%, 95.6%, 95.7%, 95.8%, 95.9%, 96.0%, 96.1%, 96.2%, 96.3%,
96.4%, 96.5%, 96.6%, 96.7%, 96.8%, 96.9%, 97.0%, 97.1%, 97.2%,
97.3%, 97.4%, 97.5%, 97.6%, 97.7%, 97.8%, 97.9%, 98.0%, 98.1%,
98.2%, 98.3%, 98.4%, 98.5%, 98.6%, 98.7%, 98.8%, 98.9% 99.0%,
99.1%, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%, 99.8%, 99.9% or
100%.
In one embodiment, a bacterium present in the composition belongs
to the same species as a bacterium disclosed herein, has at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity to a nucleic acid sequence selected from SEQ
ID NOs. 1 to 15 and retains activity against cancer/efficacy in
enhancing the effect of a therapy using an immune checkpoint
inhibitor. Such sequences include SEQ ID. Nos 16 to 29, for example
SEQ ID. Nos 16 to 20.
In one embodiment, the composition comprises or consists of one or
more of the following 15 bacteria having a 16sDNA of the following
SEQ ID Nos.:
SEQ ID No. 1 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 2 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 3 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 4 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 5 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 6 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 7 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 8 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 9 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 10 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 11 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 12 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 13 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 14 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto,
SEQ ID No. 15 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto.
Examples of the above are SEQ ID Nos. 16-29.
Thus, the composition comprises or consists of a population of
bacteria that belong to one or more of the 15 bacterial having a
16sDNA as shown above.
In one embodiment, the composition does not include
Faecalibacterium prausnitzii (e.g. SEQ ID No. 15). In one
embodiment, the composition does not include Alistipes indistinctus
(e.g. SEQ ID No. 5), Alistipes obesi (e.g. SEQ ID No. 4 or 16)
and/or Alistipes timonensis (e.g. SEQ ID No. 10).
In one embodiment, the composition comprises a consortium as shown
in Table 3.
Thus, in one embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 2 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 3 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 4 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 5, or a 16S rDNA sequence having at
least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,
99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.
6 or a 16S rDNA sequence having at least 90% e.g. at least 91%,
92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity
thereto, bacteria having SEQ ID No. 7 or a 1S rDNA sequence having
at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,
99%; e.g. 97% or 98.7% identity thereto; bacteria having SEQ ID No.
8 or a 1S rDNA sequence having at least 90% e.g. at least 91%, 92%,
93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity
thereto or a 16S rDNA sequence having at least 90% e.g. at least
91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%
identity thereto and bacteria having SEQ ID No. 9 or a 1S rDNA
sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%,
96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or a 16S
rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,
95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto
(consortium 2 in Table 3).
In one embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 2 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 3 or a 1S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 6 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 7, or a 1S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 8 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 9 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto; bacteria having SEQ ID No. 11 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or
a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,
93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity
thereto; bacteria having SEQ ID No. 12 or a 16S rDNA sequence
having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,
97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or a 16S rDNA
sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%,
96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria
having SEQ ID No. 13 or a 16S rDNA sequence having at least 90%
e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97%
or 98.7% identity thereto or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 14 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or
a 16S rDNA sequence having at least 90% e.g. at least 91%, 92%,
93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity
thereto and bacteria having SEQ ID No. 15 or a 16S rDNA sequence
having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,
97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or a 16S rDNA
sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%,
96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto (consortium
3 in Table 3).
In another embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, SEQ ID No. 2 or a 16S rDNA sequence
having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,
97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having
SEQ ID No. 3 or a 18S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto, bacteria having SEQ ID No. 6 or a 16S rDNA
sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%,
96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria
having SEQ ID No. 7 or a 16S rDNA sequence having at least 90% e.g.
at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto, bacteria having SEQ ID No. 8 or a 16S rDNA
sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%,
96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria
having SEQ ID No. 9 or a 16S rDNA sequence having at least 90% e.g.
at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto, bacteria having SEQ ID No. 11 or a 16S rDNA
sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%,
96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria
having SEQ ID No. 14 or a 16S rDNA sequence having at least 90%
e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97%
or 98.7% identity thereto (consortium 4 in Table 3).
In another embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 7 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 8 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 9 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 13 or a 16S rDNA sequence having at
least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,
99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.
16 or a 16S rDNA sequence having at least 90% e.g. at least 91%,
92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity
thereto, bacteria having SEQ ID No. 17 or a 16S rDNA sequence
having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,
97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having
SEQ ID No. 18 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto and bacteria having SEQ ID No. 20 or a 16S
rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,
95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto
(consortium 5 in Table 3).
In another embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 2 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 7 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 9 or a
18S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 13 or a 16S rDNA sequence having at
least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,
99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.
16 or a 16S rDNA sequence having at least 90% e.g. at least 91%,
92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity
thereto, bacteria having SEQ ID No. 18 or a 16S rDNA sequence
having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,
97%, 98%, 99%; e.g. 97% or 98.7% identity thereto, bacteria having
SEQ ID No. 19 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto and bacteria having SEQ ID No. 20 or a 16S
rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%, 94%,
95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto
(consortium 6 in Table 3).
In another embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 2 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 7 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 9 or a
18S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 18 or a 16S rDNA sequence having at
least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,
99%; e.g. 97% or 98.7% identity thereto and bacteria having SEQ ID
No. 19 or a 16S rDNA sequence having at least 90% e.g. at least
91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7%
identity thereto (consortium 7 in Table 3).
In another embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 2 or a
168S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto
and, bacteria having SEQ ID No. 7 or a 16S rDNA sequence having at
least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,
99%; e.g. 97% or 98.7% identity thereto (consortium 8 in Table
3).
In another embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto and bacteria having SEQ ID No. 2 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto
(consortium 9 in Table 3).
Thus, in one embodiment, the composition comprises or consists of
bacteria having SEQ ID No. 1 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 2 or a
168S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 3 or a 16S rDNA sequence having at least
90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g.
97% or 98.7% identity thereto, bacteria having SEQ ID No. 5 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto,
bacteria having SEQ ID No. 7, or a 16S rDNA sequence having at
least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%,
99%; e.g. 97% or 98.7% identity thereto, bacteria having SEQ ID No.
10 or a 16S rDNA sequence having at least 90% e.g. at least 91%,
92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e g. 97% or 98.7% identity
thereto, bacteria having SEQ ID No. 11 or a 16S rDNA sequence
having at least 90% e.g. at least 91%, 92%, 93%, 94%, 95%, 96%,
97%, 98%, 99%; e.g. 97% or 98.7% identity thereto; bacteria having
SEQ ID No. 13 or a 16S rDNA sequence having at least 90% e.g. at
least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or
98.7% identity thereto or a 16S rDNA sequence having at least 90%
e.g. at least 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97%
or 98.7% identity thereto and bacteria having SEQ ID No. 14 or a
16S rDNA sequence having at least 90% e.g. at least 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity thereto or
a 168S rDNA sequence having at least 90% e.g. at least 91%, 92%,
93%, 94%, 95%, 96%, 97%, 98%, 99%; e.g. 97% or 98.7% identity
thereto (consortium 10 in Table 3).
With reference to the percentage identities recited for the
embodiments of the compositions above, in one embodiments sequence
identity is at least 98.7% or 99%. It will be understood that where
Table 1 provides multiple sequences for a single species, any of
these sequences can be used according to the above embodiments.
In one example, species used in the composition are identified
based on their 16S rDNA sequence (e.g., full-length sequence, or
partial sequence). In some cases, strains of bacterial species
useful in an invention, e.g., strains of the species disclosed
herein, can be obtained from a public biological resource center
such as the ATCC (atcc.org), the DSMZ (dsmz.de), or the Riken
BioResource Center (en.brc.riken.jp). 16s rDNA sequences useful for
identifying species or other aspects of the invention can be
obtained from public databases, e.g., the Human Microbiome Project
(HMP) web site or GenBank.
A skilled person would appreciate that the compositions may include
one or more than one strain of a particular bacterial species as
listed in Table 1. For example, the composition of the invention
comprises more than one bacterial strain for a species. For
example, in some embodiments, the composition of the invention
comprises more than one strain from within the same species (e.g.
more than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40 or
45 strains). In another embodiment, the composition of the
invention comprises one bacterial strain for each species.
In one embodiment, the bacteria of the composition are capable of
colonising the gastrointestinal tract of a subject. In one
embodiment, the bacteria of the composition are capable of
sustained engraftment in the gastrointestinal tract of a
subject.
In one embodiment, the composition has one or more of the following
characteristics: The composition has an immunostimulatory effect;
The composition is effective in treating and/or preventing cancer
in a subject, tissue or cell. e.g. when used together with a
checkpoint inhibitor therapy; The composition is effective in
treating and/or preventing an infectious disease in a subject,
tissue or cell; Administration of the composition to a subject,
tissue or cell induces an immune response in a subject and/or
increases the efficacy according to an anti-cancer therapy that
includes an immune checkpoint inhibitor, Administration of the
composition to a subject, tissue or cell enhances CD8+ response;
Administration of the composition to a subject, tissue or cell
enhances immune checkpoint blockade; Administering of the
composition maintains or induces responsiveness of a tumour an
immune checkpoint; Administration of the composition to a subject,
tissue or cell increases the number or activity of a cell type of
the immune system, e.g. T cells, B cells, dendritic cells,
macrophages, neutrophils, NK cells, plasmacytoid dendritic cells
and combinations thereof; Administration of the composition to a
subject, tissue or cell shifts a ratio of immune cells in the
subject in favor of a cell type capable of suppressing growth of a
tumour e.g. T cells, cytotoxic T lymphocytes, T helper cells,
natural killer (NK) cells, natural killer T (NKT) cells,
plasmacytoid dendritic cells, anti-tumour macrophages, B cells,
dendritic cells, and combinations thereof and/or Administration of
the composition to a subject, tissue or cell shifts a ratio of
immune cells in the subject against a cell type capable of
protecting a tumour e.g. myeloid-derived suppressor cells (MDSCs),
regulatory T cells (Tregs), tumour associated neutrophils (TANs),
M2 macrophages, tumour associated macrophages (TAMs), and a
combination thereof; Administration of the composition to a
subject, tissue or cell increases the abundance/level of bacteria
in the subject which discourages cancer/tumour growth, spread,
and/or evasion of treatment/immune response; Administration of the
composition to a subject, tissue or cell increases the abundance of
bacteria in the subject tissue or cell which creates an environment
or microenvironment (e.g., metabolome) that is conducive to the
treatment of cancer and/or inhibits cancer/tumour growth.
The subject may be a human or an animal in an animal model, for
example a mouse model. In vitro models can also be used for testing
efficacy, e.g. tissue or cell-based models. Suitable models and
assays are also shown in the examples.
As used herein, an "immune response" refers to the action of a cell
of the immune system (e.g., T lymphocytes, B lymphocytes, natural
killer (NK) cells, macrophages, eosinophils, mast cells, dendritic
cells, neutrophils, etc.) and soluble macromolecules produced by
any of these cells or the liver (including antibodies, cytokines,
and complement) that results in selective targeting, binding to,
damage to, destruction of, and/or elimination from a subject of
invading pathogens, cells or tissues infected with pathogens, or
cancerous or other abnormal cells. This can be measured by
assessing suitable markers or cell types.
As used herein, the term "immunotherapy" refers to the treatment or
prevention of cancer by a method comprising inducing, enhancing,
suppressing or otherwise modifying an immune response.
The bacterial isolates can be isolated and cultured as described in
WO2013/171515 or WO2017/182796, both incorporated herein by
reference. In one embodiment, bacterial strains are cultured and
grown individually and then combined in the composition.
A bacterial isolate used in the composition is preferably a
non-pathogenic strain. In other words, the bacterium preferably
does not cause a disease in a healthy human individual when
administered to said individual.
In one embodiment, each bacterium present in the composition is
susceptible to treatment with one or more antibiotics. In other
words, the bacterium is not resistant to treatment with at least
one antibiotic. This allows antibiotic treatment of an individual
in the event that one or more of the bacteria included in a
therapeutic composition administered to the individual cause
disease in the individual, contrary to expectations. Thus, in one
embodiment, the bacterium is susceptible to treatment with one or
more antibiotics selected from the group consisting of: a
beta-lactam, fusidic acid, elfamycin, aminoglycoside, fosfomycin,
tunicamycin metronidazole and/or vancomycin. In vitro and in silico
methods for screening bacteria for antibiotic resistance are known
in the art.
In one embodiment, the isolated bacterium included in the
compositions may not comprise one or more genes encoding one or
more virulence factors and/or preferably does not produce one or
more virulence factors. Virulence factors in this context are
properties which enhance the potential of a bacterium to cause
disease in an individual. Virulence factors include the production
of bacterial toxins, such as endotoxins and exotoxins by a
bacterium, as well as the production of hydrolytic enzymes that may
contribute to the pathogenicity of the bacterium. Methods for
screening bacteria for genes encoding virulence factors are known
in the art.
In some embodiments, one or more of the bacterial strains are
human-derived bacteria, meaning the one or more bacterial strains
were obtained from or identified from a human or a sample therefrom
(e.g., a human donor). In some embodiments of the compositions
provided herein, all of the bacterial strains are human-derived
bacteria. In some embodiments of the compositions provided herein,
the bacterial strains are derived from more than one human
donor.
The bacterial strains used in the live bacterial products provided
herein generally are isolated from the microbiome of healthy
individuals, e.g. from human faeces, but in some cases may not be
from healthy individuals. In some embodiments, the live bacterial
products include strains originating from a single individual. In
some embodiments, the live bacterial products include strains
originating from multiple individuals. In some embodiments, the
bacterial strains are obtained from multiple individuals, isolated
and grown up individually. The bacterial compositions that are
grown up individually may subsequently be combined to provide the
compositions of the disclosure. It should be appreciated that the
origin of the bacterial strains of the live bacterial products
provided herein is not limited to the human microbiome from a
healthy individual.
Isolation and characterisation can be achieved using standard
methods in the art. For example, the V4-V5 region of the 16S rRNA
encoding gene can be amplified and sequenced. Sequences can then be
aligned and compared to the 16S sequences provided herein for the
bacterial isolates. Sequence protocols and alignment software are
well known in the art.
In some cases, strains of bacterial species useful in an invention,
e.g., strains of the species disclosed herein, can be obtained from
a public biological resource centre as described above.
In some embodiments in which the composition of the invention
comprises more than one bacterial strain or species as listed
herein, the individual bacterial strains or species may be for
separate, simultaneous or sequential administration. For example,
the composition may comprise bacteria from all or a subset of the
species listed in Table 1, or the bacterial strains or species are
selected from those listed in Table 1, but may be stored separately
and be administered separately, simultaneously or sequentially. In
some embodiments, the more than one bacterial strain or species are
stored separately, but are mixed together prior to use.
As explained herein, the bacterial compositions of the invention
have therapeutic effects when administered to a subject and can be
used in the treatment or prevention of cancer. Thus, the
compositions as described herein are therapeutic compositions.
Thus, the invention also extends to pharmaceutical compositions
comprising a composition of bacteria as described herein. This may
include further ingredients, for example a vaccine.
In one embodiment, the composition may comprise a pharmaceutically
acceptable excipient, carrier, buffer, stabilizer or other
materials well known to those skilled in the art. Such materials
should be non-toxic and should not interfere with the efficacy of
the isolated bacteria present in the therapeutic composition. The
precise nature of the pharmaceutically acceptable excipient or
other material will depend on the route of administration, which
may be oral or rectal. Many methods for the preparation of
therapeutic compositions are known to those skilled in the art.
The bacterial compositions of the invention may comprise a
prebiotic, a pharmaceutically acceptable carrier, insoluble fibre,
a buffer, an osmotic agent, an anti-foaming agent and/or a
preservative. Particular examples of excipients included in the
composition are disclosed below.
Prebiotics may provide nutrients for the isolated bacteria present
in the bacterial composition to assist their early growth and
colonisation after administration to the individual. Any prebiotic
known in the art may be used. Non-limiting examples of prebiotics
include oligosaccharides, e.g., fructooligosaccharides such as
oligofructose and inulin, mannan oligosaccharides and
galactooligosaccharides, soluble, oligofructose-enriched inulin and
soluble fibre. Insoluble fibre may be included in the therapeutic
composition as a carrier, e.g., to provide protection during
transit or storage. A buffer may be included in the bacterial
composition to promote the viability of the isolated bacteria
present. An anti-fungal agent may be included in the bacterial
composition as a preservative.
In one embodiment, the therapeutic bacterial compositions may
comprise no other active ingredient other than the bacterial
isolates as described herein, including no other isolated
bacterium, and optionally a prebiotic. Thus, the active ingredient
of the therapeutic composition may consist of the group of
bacterial isolates as described herein, and optionally a
prebiotic.
The bacterial compositions of the invention can be administered to
a subject in a variety of ways as described in more detail
elsewhere herein, including in the form of a capsule, tablet, gel
or liquid.
The bacterial compositions of the invention may be for oral or
rectal administration to the subject. Where the composition is for
oral administration, the composition may be in the form of a
capsule, or a tablet. Where the therapeutic composition is for
rectal administration, the therapeutic composition may be in the
form of an enema, tablet or capsule. The preparation of suitable
capsules, tablets and enemas is well-known in the art. The capsule
or tablet may comprise an enteric coating to protect the capsule or
tablet from stomach acid. For example, the capsule or tablet may be
enteric-coated, pH dependent, slow-release, and/or
gastro-resistant. Such capsules and tablets are used, for example,
to minimize dissolution of the capsule or tablet in the stomach but
allow dissolution in the small intestine. When intended for oral
administration, the composition can be in solid or liquid form,
where semi-solid, semi-liquid, suspension and gel forms are
included within the forms considered herein as either solid or
liquid.
As a solid composition for oral administration, the composition can
be formulated into a powder, granule, compressed tablet, pill,
capsule, chewing gum, wafer or the like. Such a solid composition
typically contains one or more inert diluents. In addition, one or
more of the following can be present: binders such as
carboxymethylcellulose, ethyl cellulose, microcrystalline
cellulose, or gelatin, excipients such as starch, lactose or
dextrins, disintegrating agents such as alginic acid, sodium
alginate, corn starch and the like; lubricants such as magnesium
stearate, glidants such as colloidal silicon dioxide, sweetening
agents such as sucrose or saccharin, a flavoring agent such as
peppermint, methyl salicylate or orange flavoring; and a coloring
agent. When the composition is in the form of a capsule (e. g. a
gelatin capsule), it can contain, in addition to materials of the
above type, a liquid carrier such as polyethylene glycol,
cyclodextrin or a fatty oil.
When intended for oral administration, a composition can comprise
one or more of a sweetening agent, preservatives, dye/colorant and
flavor enhancer. In a composition for administration by injection,
one or more of a surfactant, preservative, wetting agent,
dispersing agent, suspending agent, buffer, stabilizer and isotonic
agent can also be included.
The bacterial composition may include a pharmaceutically acceptable
carrier or vehicle that can be particulate, so that the
compositions are, for example, in tablet or powder form. The term
"carrier" refers to a diluent, adjuvant or excipient, with which
the composition is administered. Such pharmaceutical carriers can
be liquids, such as water and oils, including those of petroleum,
animal, vegetable or synthetic origin, such as peanut oil, soybean
oil, mineral oil, sesame oil and the like. The carriers can be
saline, gum acacia, gelatin, starch paste, talc, keratin, colloidal
silica, urea, and the like. In addition, auxiliary, stabilizing,
thickening, lubricating and coloring agents can be used. In one
embodiment, the composition and pharmaceutically acceptable
carriers are sterile. Saline solutions and aqueous dextrose and
glycerol solutions can also be employed as liquid carriers,
particularity for injectable solutions. Suitable pharmaceutical
carriers also include excipients such as starch, glucose, lactose,
sucrose, gelatin, malt, rice, flour, chalk, silica gel, sodium
stearate, glycerol monostearate, talc, sodium chloride, dried skim
milk, glycerol, propylene, glycol, water, ethanol and the like. The
present compositions, if desired, can also contain minor amounts of
wetting or emulsifying agents, or pH buffering agents.
The compositions can take the form of one or more dosage units. In
an embodiment, the dose unit comprises at least 1.times.10.sup.3,
1.times.10.sup.4, 1.times.10.sup.5, 1.times.10.sup.6,
1.times.10.sup.7, 1.times.10.sup.8, 1.times.10.sup.9,
1.times.10.sup.10, 1.times.10.sup.11, 1.times.10.sup.12,
1.times.10.sup.13 or greater than 1.times.10.sup.13 colony forming
units (cfu) of vegetative bacterial cells. In an embodiment, the
dose unit comprises a pharmaceutically acceptable excipient, an
enteric coating or a combination thereof. The bacterial isolates or
composition may be provided at a suitable dose.
Treatments or specific processes can be applied to improve the
stability or viability of the bacterial isolates in the
composition. The bacterial composition can be applied in a dry form
or in a wet from. The bacterial composition may be lyophilized. The
lyophilized therapeutic composition may comprise one or more
stabilisers and/or cryoprotectants. The lyophilized bacterial
composition may be reconstituted using a suitable diluent prior to
administration to the individual.
Then invention also relates to a pharmaceutical composition
comprising one or more bacteria of selected from the bacterial
species of Table 1 or comprising a composition as described herein
and further comprising an effective amount of an immune checkpoint
inhibitor.
Immune checkpoints are regulatory pathways within the immune system
that are involved in maintaining immune homeostasis (e.g.,
self-tolerance, modulating the duration and extent of an immune
response) to minimize cellular damage due to aberrant immune
responses. Inhibitors of immune checkpoints, herein referred to as
"immune checkpoint inhibitors," specifically inhibit immune
checkpoints and may have a stimulatory or inhibitory effect on the
immune response.
In one embodiment, the immune checkpoint inhibitor is an antibody
or fragment thereof, an interfering nucleic acid molecule or
another chemical entity.
A number of checkpoint inhibitors are known in the art and a number
of treatments have been approved by regulatory authorities,
including antibody treatments, whilst others, including treatments
with monoclonal antibodies or antibody fragments, such as single
domain antibodies, have shown efficacy across a wide range of
cancers.
In one embodiment, the immune checkpoint inhibitor inhibits PD-1
activity, i.e. acts as PD-1 antagonist.
"PD-1 antagonist" or "PD-1 inhibitor" means any chemical compound
or biological molecule that blocks binding of PD-L1 expressed on a
cancer and or immune cell to PD-1 expressed on an immune cell (T
cell, B cell or NKT cell) and preferably also blocks binding of
PD-L2 expressed on a cancer and or immune cell to the immune-cell
expressed PD-1.
In one embodiment, the immune checkpoint inhibitor is a PD-1
inhibitor, PD-L1 inhibitor or PD-L2 inhibitor, e.g. an anti PD-1
antibody or anti PD-L1 or anti PD-L2 antibody. In one embodiment,
the immune checkpoint inhibitor is an anti PD-1 antibody. In one
embodiment, the immune checkpoint inhibitor is an anti PD-1 or
PD-L1 antibody optionally selected from nivolumab (MDX-1106,
MDX-1106-04, ONO-4538, or BMS-936558), pembrolizumab (Trade name
KEYTRUDA.RTM. formerly lambrolizumab, also known as Merck 3745,
MK-3475 or SCH-900475), cemiplimab, avelumab, durvalumab,
atezolizumab, spartalizumab, camrelizumab, sintilimab,
tislelizumab, pidilizumab or toripalimab.
In one embodiment, the immune checkpoint inhibitor is an
anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4
inhibitor), i.e. inhibits the activity of CTLA-4. CTLA-4 (CD152) is
a B7/CD28 family member that inhibits T cell functions with NCBI
Gene ID: 1493. CTLA-4 mAbs or CTLA-4 ligands can prevent CTLA-4
from binding to its native ligands, thereby blocking the
transduction of the T-cell negative regulating signal by CTLA-4 and
enhancing the responsiveness of T-cells to various antigens. In
this aspect, results from in vivo and in vitro studies are
substantially in concert.
The CTLA4 inhibitor can be a CTLA4 antibody, optionally Ipilimumab
or Tremelimumab.
In one embodiment, the immune checkpoint inhibitor is an anti-TGIT,
anti-LAG3 or anti-TIM3 agent, e.g. and antibody. The checkpoint
targets listed herein are not limiting and a skilled person would
understand that other checkpoint targets are also within the scope
of the invention and may be inhibited.
It should further be appreciated that multiple immune checkpoint
inhibitors may be used in the methods, compositions, and kits
disclosed herein.
In some embodiments, the cancer immunotherapy agent comprises an
anticancer vaccine (also referred to herein as a cancer vaccine).
Cancer vaccines generally act to increase an immune response to
cancer cells. For example, cancer vaccines include cancer
antigen(s) that act to induce or stimulate an immune response
against cells bearing the cancer antigen(s). The immune response
induced or stimulated can include an antibody (humoral) immune
response and/or a T-cell (cell-mediated) immune response.
Unless otherwise specified, the term PD-1 as used herein refers to
human PD-1. The terms "Programmed Death 1", "Programmed Cell Death
1", "Protein PD-1", "PD-1", PD1," "PDCD1", "hPD-1" and "hPD-1" are
used interchangeably, and include variants, isoforms, species
homologs of human PD-1. The term PD-1 antibody or antibody fragment
refers to a molecule capable of specifically binding to the human
PD-1 antigen and antagonising PD-1 action. Human PD-1 amino acid
sequences can be found in NCBI Locus No.: NP_005009. Human PD-L1
and PD-L2 amino acid sequences can be found in NCBI Locus No.:
NP_054862 and NP_079515, respectively.
The term "antibody" as used herein broadly refers to any
immunoglobulin (Ig) molecule, or antigen binding portion thereof,
comprised of four polypeptide chains, two heavy (H) chains and two
light (L) chains, or any functional fragment, mutant, variant, or
derivation thereof, which retains the essential epitope binding
features of an Ig molecule. Such mutant, variant, or derivative
antibody formats are known in the art. The antibody may be mono or
multispecific, e.g. bispecific. The antibody may be administered in
combination with another antibody therapy, e.g. another antibody
that targets a checkpoint inhibitor or in combination with another
anti-cancer therapy, e.g. chemotherapy and targeted therapies,
surgery and/or radiotherapy.
In a full-length antibody, each heavy chain is comprised of a heavy
chain variable region or domain (abbreviated herein as HCVR) and a
heavy chain constant region. The heavy chain constant region is
comprised of three domains, CH1, CH2 and CH3. Each light chain is
comprised of a light chain variable region or domain (abbreviated
herein as LCVR) and a light chain constant region. The light chain
constant region is comprised of one domain, CL.
The heavy chain and light chain variable regions can be further
subdivided into regions of hypervariability, termed complementarity
determining regions (CDR), interspersed with regions that are more
conserved, termed framework regions (FR). Each heavy chain and
light chain variable region is composed of three CDRs and four FRs,
arranged from amino-terminus to carboxy-terminus in the following
order: FR1, CDR1, FR2, CDR2, FR3, CDR3, FR4.
Immunoglobulin molecules can be of any type (e.g., IgG, IgE, IgM,
IgD, IgA and IgY), class (e.g., IgG 1, IgG2, IgG 3, IgG4, IgA1 and
IgA2) or subclass.
The term antibody as used herein includes antibody fragments, such
as F(ab')2, Fab, Fv, scFv, a heavy chain only antibody, single
domain antibodies (V.sub.H, V.sub.L, V.sub.HH) or an antibody
mimetic protein. Various antibody formats have been shown to show
efficacy against checkpoint inhibitors, including single domain
antibodies (e.g. Yu S et al. Nanobodies targeting immune checkpoint
molecules for tumor immunotherapy and immunoimaging. Int J Mol Med.
2021; 47(2):444-454).
scFv fragments (.about.25 kDa) consist of the two variable domains,
V.sub.H and V.sub.L. Naturally, V.sub.H and V.sub.L domain are
non-covalently associated via hydrophobic interaction and tend to
dissociate. However, stable fragments can be engineered by linking
the domains with a hydrophilic flexible linker to create a single
chain Fv (scFv). The smallest antigen binding fragment is the
single variable fragment, namely the V.sub.H or V.sub.L domain.
Binding to a light chain/heavy chain partner respectively is not
required for target binding. Such fragments are used in single
domain antibodies. A single domain antibody (.about.12 to 15 kDa)
therefore has either the V.sub.H or V.sub.L domain.
The antibody may be human, humanised or chimeric. A chimeric
antibody is a recombinant protein that contains the variable
domains including the complementarity determining regions (CDRs) of
an antibody derived from one species, preferably a rodent antibody,
while the constant domains of the antibody molecule are derived
from those of a human antibody.
A humanized antibody is a recombinant protein in which the CDRs
from an antibody from one species; e.g., a rodent antibody, are
transferred from the heavy and light variable chains of the rodent
antibody into human heavy and light variable domains (e.g.,
framework region sequences). The constant domains of the antibody
molecule are derived from those of a human antibody. In certain
embodiments, a limited number of framework region amino acid
residues from the parent (rodent) antibody may be substituted into
the human antibody framework region sequences.
Checkpoint inhibitors are not limited to antibodies. In one
embodiment, the immune checkpoint inhibitor is an interfering
nucleic acid molecule, optionally wherein the interfering nucleic
acid molecule is an siRNA molecule, an shRNA molecule or an
antisense RNA molecule.
In one embodiment, the immune checkpoint inhibitor is a small
molecule or PROteolysis TArgeting Chimera (PROTAC), alternative
scaffold protein, biologics or other immune checkpoint inhibitor.
In one embodiment, the immune checkpoint inhibitor is an
interfering nucleic acid molecule. In one embodiment, the
interfering nucleic acid molecule is an siRNA molecule, an shRNA
molecule or an antisense RNA molecule. In one embodiment, the
immune checkpoint inhibitor is a small molecule or a PROteolysis
TArgeting Chimera (PROTAC) or other immune checkpoint inhibitor.
Examples that small molecules can be used as checkpoint inhibitors
is provided by research on sulfamonomethoxine and sulfamethizole.
Exemplary small molecule compounds that inhibit PD-L1 are disclosed
in U.S. Pat. No. 9,850,225 incorporated herein by reference. A
small molecule currently in human clinical trials is a molecule
called Ca-170, which inhibits both the PD-L1 pathway and the
V-domain Ig suppressor of the T-cell activation (VISTA)
pathway.
In one embodiment, the immune checkpoint inhibitor is a peptide
inhibitor. An example is the peptide antagonist. (D)PPA-1, which
blocks the PD-1/PD-L1 interaction and decreases tumor growth in
vivo (Chang H. N et al. Blocking of the PD-1/PD-L1 interaction by a
D-Peptide Antagonist for Cancer Immunotherapy. Angew. Chem. Int.
Ed. 2015; 54:11760-11764). Another peptide inhibitor is PL120131,
shown to act as a competitive inhibitor of PD-L1 (Magiera-Mularz K.
et al Bioactive Macrocyclic Inhibitors of the PD-1/PD-L1 Immune
Checkpoint. Angew. Chem. Int. Ed. 2017; 56:13732-13735) and TPP-1
(Li C., Zhang N et al, Peptide Blocking of PD-1/PD-L1 Interaction
for Cancer Immunotherapy. Cancer Immunol. Res. 2018;
6:178-188).
In another aspect, there is provided a bacterial composition
described herein for use in the treatment of disease. e.g. cancer.
In another aspect, there is provided the use of a bacterial
composition described herein in the manufacture of a medicament for
the treatment or prevention of a disease, e.g. cancer.
In another aspect, there is provided a method for treating or
preventing a disease comprising administering a bacterial
composition described herein to a subject. In another aspect, there
is provided a method for treating or preventing a disease in a
subject comprising modulating the level of, e.g. Increasing the
level/relative abundance of one or more bacterium selected from B1,
B2, B3, B4, B5, B8, B7, B8, B9, B10, B11, B12, B13, B14 and/or B15
as shown in Table 1 or a subset thereof in a subject. In one
embodiment, the subset comprises or consists of bacteria selected
from 1, 2, 3, 4, 5, 8, 7, 8, 9, 10, 11, 12, 13, 14 or 15 bacterial
species shown in Table 1. Modulating the level according to one or
more bacterium in the subject enhances an immune response by the
subject and/or inhibits immune evasion by the cancer and/or
increases efficacy according to an anti-cancer treatment with an
immune checkpoint inhibitor. In one embodiment, the method
comprises administering a composition as described herein.
As explained below, the level/abundance can be compared to a
reference value from a reference subject or population of
subjects.
In one embodiment, the disease is cancer. In one embodiment, the
cancer is melanoma. "Melanoma" is taken to mean a tumour arising
from the melanocytic system of the skin and other organs.
Non-limiting examples of melanomas are Harding-Passey melanoma,
juvenile melanoma, lentigo maligna melanoma, malignant melanoma,
acral-lentiginous melanoma, amelanotic melanoma, benign juvenile
melanoma, Cloudman's melanoma, S91 melanoma, nodular melanoma,
subungual melanoma, Cutaneous melanoma, uveal/intraocular melanoma
and superficial spreading melanoma.
The compositions of the present invention are particularly useful
for the treatment of cancers that are treatable by checkpoint
inhibitors.
In one embodiment, the cancer is associated with cells (e.g.,
exhausted T cells, B cells, monocytes, etc.) that express
abnormally high levels of PD-1. Other cancers include those
characterized by elevated expression of PD-1 and/or its ligands
PD-L1 and/or PD-L2.
In one embodiment, the cancer is selected from a cancer that has
high levels of cancer-associated genetic mutations and/or high
levels of expression of tumour antigens. In another embodiment, the
cancer is selected from a cancer known to be immunogenic or that is
able to become immunogenic upon treatment with other cancer
therapies. In a further embodiment the cancer can be selected from
a cancer generally treated by non-immunological therapies, such as
chemotherapy, in which the patient's immune system is likely to
have a role.
The cancer can be selected from a solid or non-solid tumour. For
example, in addition to melanoma, the cancer may be selected from
another skin cancer or from bone cancer, pancreatic cancer, cancer
of the head or neck, cutaneous or intraocular malignant melanoma,
uterine cancer, ovarian cancer, rectal cancer, cancer of the anal
region, stomach cancer, testicular cancer, breast cancer, brain
cancer, carcinoma of the fallopian tubes, carcinoma of the
endometrium, carcinoma of the cervix, carcinoma of the vagina,
carcinoma of the vulva, cancer of the esophagus, cancer of the
small intestine, cancer of the endocrine system, cancer of the
thyroid gland, cancer of the parathyroid gland, cancer of the
adrenal gland, kidney cancer, sarcoma of soft tissue, cancer of the
urethra, cancer of the bladder, renal cancer, lung cancer,
non-small cell lung cancer, thymoma, urothelial carcinoma leukemia,
prostate cancer, mesothelioma, adrenocortical carcinoma, lymphomas,
such as such as Hodgkin's disease, non-Hodgkin's, gastric cancer,
and multiple myelomas.
In one embodiment, the tumour is a solid tumour. Examples of solid
tumours which may be accordingly treated include breast carcinoma,
lung carcinoma, colorectal carcinoma, pancreatic carcinoma, glioma
and lymphoma. Some examples of such tumours include epidermoid
tumours, squamous tumours, such as head and neck tumours,
colorectal tumours, prostate tumours, breast tumours, lung tumours,
including small cell and non-small cell lung tumours, pancreatic
tumours, thyroid tumours, ovarian tumours, and liver tumours. Other
examples include Kaposi's sarcoma, CNS, neoplasms, neuroblastomas,
capillary hemangioblastomas, meningiomas and cerebral metastases,
melanoma, gastrointestinal and renal carcinomas and sarcomas,
rhabdomyosarcoma, glioblastoma, preferably glioblastoma multiforme,
and leiomyosarcoma. Examples of vascularized skin cancers for which
the antagonists of this invention are effective include squamous
cell carcinoma, basal cell carcinoma and skin cancers that can be
treated by suppressing the growth of malignant keratinocytes, such
as human malignant keratinocytes. In one embodiment, the cancer is
NSCL.
In one embodiment, the tumour is a non-solid tumour. Examples of
non-solid tumours include leukemia, multiple myeloma and
lymphoma.
In one aspect, the cancer is identified as a PD-1 and/or PD-L1
positive cancer or a cancer positive for another checkpoint
protein. In one aspect, the cancer is locally advanced,
unresectable, metastatic, or recurrent cancer.
Preferred cancers whose growth may be inhibited using the agents of
the invention include cancers typically responsive to
immunotherapy. Non-limiting examples of preferred cancers for
treatment include melanoma (e.g., metastatic malignant melanoma),
renal cancer (e.g. clear cell carcinoma), prostate cancer (e.g.
hormone refractory prostate adenocarcinoma), breast cancer, colon
cancer and lung cancer (e.g. non-small cell lung cancer).
As used herein, "treat", "treating" or "treatment" means inhibiting
or relieving a disease or disorder. For example, treatment can
include a postponement of development of the symptoms associated
with a disease or disorder, and/or a reduction in the severity of
such symptoms that will, or are expected, to develop with said
disease. The terms include ameliorating existing symptoms,
preventing additional symptoms, and ameliorating or preventing the
underlying causes of such symptoms. Thus, the terms denote that a
beneficial result is being conferred on at least some of the
mammals, e.g., human patients, being treated. Many medical
treatments are effective for some, but not all, patients that
undergo the treatment.
The term "subject" or "patient" refers to an animal, e.g. a human,
which is the object of treatment, observation, or diagnosis. By way
of example only, a subject includes, but is not limited to, a
mammal, including, but not limited to, a human or a non-human
mammal, such as a non-human primate, murine, bovine, equine,
canine, ovine, or feline. In one embodiment, the subject is a
cancer patient that has received prior anti-cancer treatment or is
receiving anti-cancer treatment. In one embodiment, the anti-cancer
treatment is treatment with an immune checkpoint inhibitor.
Exemplary immune checkpoint inhibitors are described herein.
The term "anti-cancer therapy" refers to any therapeutic regimen
that aims to reduce or eliminate cancer, slow the progression of
cancer, prevent or reduce the risk of cancer metastasis, and/or
reduce or prevent any one or more symptoms associated with cancer.
The anti-cancer therapies described herein involve administering
anti-cancer therapies to a subject, e.g., a subject having cancer
or at risk of having cancer.
Administration according to the method and uses above includes oral
administration or rectal administration.
In one embodiment, the subject has received prior anti-cancer
therapy with an immune checkpoint inhibitor. In one embodiment, an
anti-cancer therapy comprising an immune checkpoint inhibitor is
administered to the subject. This can be administered at the same
time as the composition of the invention, either as part of the
same medicament or as a second medicament. It can also be
administered prior or after the administration of the composition
of the invention. Other treatment schedules are also within the
scope of the invention.
In one embodiment, the immune checkpoint inhibitor is administered
before, after or at the same time as the bacterial composition. In
one embodiment, checkpoint therapy is initiated, and then
supplemented with treatment using the bacterial composition
described herein if no response is seen after 3-8 months.
In one embodiment, the immune checkpoint inhibitor is administered
after the bacterial composition. In one embodiment the immune
checkpoint inhibitor is administered by injection/infusion. In one
embodiment the injection is an intravenous, intramuscular,
intratumoural or subcutaneous injection.
Checkpoint inhibitors that can be used in accordance with the
treatment aspects are defined above. For example, the immune
checkpoint inhibitor inhibits PD-1, CTLA-4 or PD-L1 activity. In
one embodiment the immune checkpoint inhibitor is an anti PD-1,
CTLA-4 or PD-L1 antibody. In one embodiment, the anti PD-1, CTLA-4
or PD-L1 antibody is selected from nivolumab, pembrolizumab,
cemiplimab, avelumab, durvalumab, atezolizumab, Spartalizumab,
Camrelizumab, Sintilimab, Tislelizumab, Pidilizumab or Toripalimab,
Ipilimumab or Tremelimumab.
The amount of the antibody that is effective/active in the
treatment of a particular disorder or condition will depend on the
nature of the disorder or condition and can be determined by
standard clinical techniques. In addition, in vitro or in vivo
assays can optionally be employed to help identify optimal dosage
ranges. The precise dose to be employed in the compositions will
also depend on the route of administration, and the seriousness of
the disease or disorder, and should be decided according to the
judgment of the practitioner and each patient's circumstances.
Factors like age, body weight, sex, diet, time of administration,
rate of excretion, condition of the host, drug combinations,
reaction sensitivities and severity of the disease shall be taken
into account.
Typically, the amount is at least about 0.01% of an anti-PD-1,
CTL-4 or PD-L1 antibody by weight of the composition. When intended
for oral administration, this amount can be varied to range from
about 0.1% to about 80% by weight of the composition. Oral
compositions can comprise from about 4% to about 50% of the
antibody by weight of the composition.
Antibody compositions can be prepared so that a parenteral dosage
unit contains from about 0.01% to about 2% by weight of the
antibody.
For administration by injection, the composition can comprise from
about typically about 0.1 mg/kg to about 250 mg/kg of the animal's
body weight, preferably, between about 0.1 mg/kg and about 20 mg/kg
of the animal's body weight, and more preferably about 1 mg/kg to
about 10 mg/kg of the animal's body weight. In one embodiment, the
composition is administered at a dose of about 1 to 30 mg/kg, e.g.,
about 5 to 25 mg/kg, about 10 to 20 mg/kg, about 1 to 5 mg/kg, or
about 3 mg/kg. The dosing schedule can vary from e.g., once a week
to once every 2, 3, or 4 weeks.
In one embodiment, the immune checkpoint inhibitor is an
interfering nucleic acid molecule. In one embodiment, the
interfering nucleic acid molecule is an siRNA molecule, an shRNA
molecule or an antisense RNA molecule. In one embodiment, the
immune checkpoint inhibitor is a small molecule or a PROteolysis
TArgeting Chimera (PROTAC) or other immune checkpoint inhibitor,
for example as described above.
In one embodiment, the method and uses further comprise
administration of an anti-cancer therapy, e.g. a second anti-cancer
therapeutic in addition to an immune checkpoint inhibitor. The
anti-cancer therapy may include a therapeutic agent or radiation
therapy and includes gene therapy, viral therapy, RNA therapy bone
marrow transplantation, nanotherapy, targeted anti-cancer therapies
or oncolytic drugs or a combination thereof. Examples of other
therapeutic agents include other checkpoint inhibitors,
antineoplastic agents, immunogenic agents, attenuated cancerous
cells, tumour antigens, antigen presenting cells such as dendritic
cells pulsed with tumour-derived antigen or nucleic acids, immune
stimulating cytokines (e.g., IL-2, IFNa2, GM-CSF), targeted small
molecules and biological molecules (such as components of signal
transduction pathways, e.g. modulators of tyrosine kinases and
inhibitors of receptor tyrosine kinases, and agents that bind to
tumour-specific antigens, including EGFR antagonists), an
anti-inflammatory agent, a cytotoxic agent, a radiotoxic agent, or
an immunosuppressive agent and cells transfected with a gene
encoding an immune stimulating cytokine (e.g., GM-CSF),
chemotherapy. In one embodiment, the composition is used in
combination with surgery. In one embodiment, the composition is
used in combination with a stem-cell transplant therapy comprising
a peripheral blood transplant, a bone marrow transplant, a cord
blood transplant, or a skin-derived stem cell transplant.
In one embodiment, the composition is used in combination with
adoptive cell transfer (ACT). In general, adoptive cell transfer
therapy involves harvesting cells from a subject, specifically
producing or expanding a specific cell population, optionally
activating the cells, and administering the expanded cells to the
subject. In some embodiments, the desired cells are immune cells
capable of killing or eliminating cancer cells.
In some embodiments, the adoptive cell transfer therapy uses
engineered T-cell receptors or chimeric antigen receptors, which
may be referred to as CAR-T therapy. CAR-T cells include T-cells
taken from a subject that are genetically engineered to express
chimeric antigen receptors (CARs) on the cell surface. The CAR-T
cell receptors are designed to recognize a specific antigen on
cancer cells (e.g., a cancer antigen). After the CAR-T cells are
infused into the subject, the CAR-T cells recognize and kill cancer
cells that express the specific antigen on their surfaces. In some
embodiments, the CAR-T cells are autologous cells, meaning the T
cells were harvested and re-administered to the same subject. In
some embodiments, the CAR-T cells are CD8+ T cells. In some
embodiments, the CAR-T cells are allogeneic cells, meaning the T
cells were harvested from one subject (e.g., the donor) and
administered to a different subject (e.g., the recipient).
Examples of cancer antigens that may be targeted by CAR-T cells are
known in the art, and selection of a cancer antigen for targeting
will depend on factors such as the cancer that is being
targeted.
In some embodiments, the anticancer therapy involves administering
one or more costimulatory agents. In some embodiments, the
costimulatory agent is a molecule that targets one or more
costimulatory molecules, thereby modulating the immune response. In
some embodiments, the costimulatory agent enhances an anticancer
immune response, for example, by preventing the downregulation of
an immune response. A costimulatory agent may be administered alone
in a cancer therapy or in combination with one or more cancer
therapies to enhance the therapeutic effect of the cancer therapy.
In some embodiments, the costimulatory agent is an antibody that
targets CD-28, OX-40, 4-1BB, or CD40.
In one embodiment of the present invention, the composition is
administered concurrently with a chemotherapeutic agent and/or with
radiation therapy. In another specific embodiment, the
chemotherapeutic agent and/or radiation therapy is administered
prior or subsequent to administration of the composition of the
present invention, preferably at least an hour, five hours, 12
hours, a day, a week, a month, more preferably several months (e.
g. up to three months), prior or subsequent to administration of
composition of the present invention.
As used herein, a chemotherapy agent refers to a molecule (e.g.,
drug) that specifically or preferentially kills cancer cells or
prevents the proliferation of cancer cells. Chemotherapy agents can
generally be categorized based on the molecular target of the
chemotherapy agent, the mechanism of action, and/or the structure
of the agent. In some embodiments, the chemotherapy agent is an
alkylating agent, a plant alkaloid, an antitumor antibiotic, an
antimetabolite, a topoisomerase inhibitor, or other antineoplastic
agent.
In one embodiment, the chemotherapeutic agent is selected from the
group consisting of alkylating agents, alkyl sulfonates,
aziridines, an ethylenimine, a methylamelamine, an acetogenin, a
camptothecin bryostatin, cally statin, CC-1065, a cryptophycin,
dolastatin, duocarmycin, eleutherobin, pancratistatin, a
sarcodictyin, spongistatin, a nitrogen mustard, a nitrosurea, an
antibiotic, a dynemicin; a bisphosphonate, an esperamicin,
neocarzinostatin chromophore and related chromoprotein enediyne
antibiotic chromophores, an aclacinomysin, actinomycin,
authramycin, azaserine, bleomycins, cactinomycin, carabicin,
caminomycin, carzinophilin, chromomycinis, dactinomycin,
daunorubicin, detorubicin, 6-diazo-5-oxo-L-norleucine, ADRIAMYCIN
doxorubicin, epirubicin, esorubicin, idarubicin, marcellomycin, a
mitomycin, mycophenolic acid, nogalamycin, an olivomycin,
peplomycin, potfiromycin, puromycin, quelamycin, rodorubicin,
streptonigrin, streptozocin, tubercidin, ubenimex, zinostatin,
zorubicin an anti-metabolite, a folic acid analogue, a purine
analog, a pyrimidine analog, an androgen, an anti-adrenal, a folic
acid replenishes aceglatone, aldophosphamide glycoside,
aminolevulinic acid, eniluracil, amsacrine, bestrabucil,
bisantrene, edatrexate, demecolcine, diaziquone, elformithine,
elliptinium acetate, an epothilone, etoglucid, gallium nitrate,
hydroxyurea, lentinan, lonidainine, a maytansinoid, mitoguazone,
mitoxantrone, mopidanmol, nitraerine, pentostatin, phenamet,
pirarubicin, losoxantrone, podophyllinic acid, 2-ethylhydrazide,
procarbazine, PSK polysaccharide complex, razoxane, rhizoxin,
sizofuran, spirogermanium, tenuazonic acid, triaziquone,
2,2',2''-trichlorotriethylamine, a trichothecene, urethan,
vindesine, dacarbazine, mannomustine, mitobronitol, mitolactol,
pipobroman, gacytosine, arabinoside ("Ara-C"), cyclophosphamide,
thiotepa, a taxoid, ABRAXANE Cremophor-free, an albumin-engineered
nanoparticle formulation of paclitaxel and TAXOTERE doxetaxel,
chlorambucil, GEMZAR gemcitabine, 6-thioguanine, mercaptopurine,
methotrexate, a platinum analog, vinblastine, platinum, etoposide
(VP-16), ifosfamide, mitoxantrone, vincristine, NAVELBINE,
vinorelbine, novantrone, teniposide, edatrexate, daunomycin,
aminopterin, xeloda, ibandronate, irinotecan (Camptosar, CPT-11),
topoisomerase inhibitor RFS 2000; difluoromethylornithine (DMFO), a
retinoid, capecitabine, combretastatin, leucovorin (LV),
oxaliplatin, Binimetinib (Mektovi), Encorafenib (Braftovi),
lapatinib (TYKERB), an inhibitor of PKC-a, an inhibitor of Raf, an
inhibitor of H-Ras, an inhibitor of EGFR, an inhibitor of VEGF-A,
pharmaceutically acceptable salt, acid or derivative thereof, and
combinations thereof.
In some embodiments, the composition of the invention may be
administered with two or more (e.g., 2, 3, 4, 5, or more)
therapeutic agents.
In one embodiment, administration is together with an agent
involved in T-cell activation, a tumour microenvironment modifier
(TME) or a tumour-specific target.
In one embodiment, the method and uses further comprise
administering an antibiotic to the subject.
In yet another aspect, the invention provides a method of
modulating an immune response in a subject comprising administering
to the subject a composition of the invention.
In some embodiments, the individual has cancer that is resistant
(has been demonstrated to be resistant) to one or more anti-cancer
therapies. In some embodiments, resistance to anti-cancer therapy
includes recurrence of cancer or refractory cancer. Recurrence may
refer to the reappearance of cancer, in the original site or a new
site, after treatment. In some embodiments, resistance to
anti-cancer therapy includes progression of the cancer during
treatment with the anti-cancer therapy. In some embodiments, the
cancer is at early stage or at late stage.
The composition of the invention has immunostimulatory properties.
Therefore, use of the composition is not limited to the treatment
of cancer. Thus, due to the immunostimulatory properties, the
composition finds use in the treatment of any disease which
requires immunostimulation, e.g. non-cancer immunotherapies.
Immunotherapy is collectively defined as a therapeutic approach
that targets or manipulates the immune system. Ultimately,
immunotherapy aims to harness the host's adaptive and innate immune
response to effectuate long-lived elimination of diseased cells and
can be categorized broadly into passive (including adoptive and
antibody-based) and active (including vaccine therapy and
allergen-specific) approaches. Passive-mediated immunotherapy
involves the administration of ex vivo-generated immune elements
(antibodies, immune cells) to patients and does not stimulate the
host immune response, while active immunotherapy induces the
patient's immune response and results in the development of
specific immune effectors (antibodies and T cells). Immunotherapy
offers a possible modality to improve the ability to prevent or
treat infectious diseases (Naran et al, Front Microbiol. 2018; 9:
3158). Thus, in some embodiments, the disease is an infectious
disease.
The recent success of PD-1 and PD-L1 blockade in cancer therapy
illustrates the important role of the PD-1/PD-L1 pathway in the
regulation of antitumor immune responses. However, signaling
regulated by the PD-1/PD-L pathway is also associated with
substantial inflammatory effects that can resemble those in
autoimmune responses, chronic infection, and sepsis, consistent
with the role of this pathway in balancing protective immunity and
immunopathology, as well as in homeostasis and tolerance (Qin et
al, Front Immunol. 2019; 10: 2298; Rao et al, Int. J. Infect. Dis.
2017; 56: 223). Thus, in another aspect, the invention provides a
composition as described herein; e.g. comprising one or more of B1
to B15 as in table 1, e.g. a composition with one or more bacterial
isolate having a 16SrDNA having a sequence selected from SEQ ID
Nos. 1 to 15 or a sequence with at least 97%, 98%, 98.7% or 99%
sequence identity thereto, e.g. SEQ ID Nos. 16-29, for use in the
treatment of an infectious disease. Also provided is a method for
the treatment of an infectious disease comprising administering a
composition of the invention to a subject. Also covered is a
composition as described herein for use in the manufacture of a
medicament for the treatment of an infectious disease.
An infectious disease may be a viral, fungal and bacterial
infection. The infectious disease may be a chronic infectious
disease. Non-limiting examples include human immunodeficiency virus
(HIV), hepatitis B (HBV), hepatitis C (HCV), JC (John Cunningham)
virus/progressive multifocal leukoencephalopathy and
tuberculosis.
Treatment of infections with the composition of the invention can
be as co-therapy with an immunotherapy, for example an immune
checkpoint inhibitor, other anti-viralS or anti-infectives.
In another aspect, the invention provides a composition as
described herein, e.g. comprising one or more of B1 to B15 as in
table 1, e.g. a composition with one or more bacterial isolate
having a 16S rDNA having a sequence selected from SEQ ID Nos. 1 to
15 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto, for use as a vaccine adjuvant. Also provided is a
method for increasing vaccine efficacy comprising administering a
composition as described herein, e.g. comprising one or more of B1
to B15 as in Table 1, e.g. a composition with one or more bacterial
isolate having a 16S rDNA having a sequence selected from SEQ ID
Nos. 1 to 15 or a sequence with at least 97%, 98%, 98.7%, 99% or
100% sequence identity thereto, e.g. SEQ ID Nos. 16-29, to a
subject. Said subject may receive a vaccine before, after or
concurrently with administration of the bacterial composition.
Administration may be in a "therapeutically effective amount", this
being sufficient to show benefit to the individual. Such benefit
may be at least amelioration of at least one symptom. Thus
"treatment" of a specified disease refers to amelioration of at
least one symptom. The actual amount administered, and rate and
time-course of administration, will depend on the nature and
severity of what is being treated, the particular patient being
treated, the clinical condition of the individual patient, the site
of delivery of the composition, the type of therapeutic
composition, the method of administration, the scheduling of
administration and other factors known to medical practitioners.
Prescription of treatment, e.g. decisions on dosage etc., is within
the responsibility of general practitioners and other medical
doctors and may depend on the severity of the symptoms and/or
progression of a disease being treated. A therapeutically effective
amount or suitable dose of a therapeutic composition of the
invention can be determined by comparing its in vitro activity and
in vivo activity in an animal model. Methods for extrapolation of
effective dosages in mice and other test animals to humans are
known. The precise dose will depend upon a number of factors,
including whether the therapeutic composition is for prevention or
for treatment.
In one embodiment of the methods which require administration of
the composition, the method includes the further step of detecting
the presence of one or more of the bacterial strain that has been
administered in the subject subsequent to administration. Methods
for detection include for example detecting a 16S nucleic acid
sequence as defined herein of at least one administered bacterial
isolate in said subject.
The composition of the present invention may be prepared by a
method comprising culturing the two or more isolated bacteria
present in the composition in a suitable medium or media. Media and
conditions suitable for culturing the bacteria to be included in
the therapeutic composition of the present invention are described
in detail elsewhere herein. For example, a method of preparing a
therapeutic composition according to the present invention may
comprise the steps of:
(i) culturing a first isolated bacterium;
(ii) culturing a second and optionally a further isolated
bacterium; and
(iii) mixing the bacteria obtained in (i) and (ii) to prepare the
therapeutic composition.
The isolated bacteria to be included in the composition may be
cultured in separate steps. In other words, a separate culture of
each bacterium to be included in the therapeutic composition is
preferably prepared. This allows the growth of each bacterium to be
evaluated and the amount of each bacterium to be included in the
pharmaceutical composition to be controlled as desired. The
bacteria cultured in steps (i) and (ii) preferably have distinct
16S nucleic acid sequences, that is 16S nucleic acid sequences that
share less than 99%, 98%, 97%, 96% or 95% sequence identity.
The above method may include steps of culturing each isolated
bacterium which is to be included in the composition.
The method may optionally comprise one or more further steps in
which the bacteria are mixed with one or more additional
ingredients, such as a pharmaceutically acceptable excipient,
prebiotic, carrier, insoluble fibre, buffer, osmotic agent,
antifoaming agent, and/or preservative. In addition, or
alternatively, the method may comprise suspending the bacteria
obtained in (i) and optionally (i) in a chemostat medium, or
saline, e.g. 0.9% saline. The bacteria obtained in (i) and
optionally (ii) may be provided under a reduced atmosphere, such as
N2, CO2, H2, or a mixture thereof, e.g. N2:CO2:H2. The gases may be
present in appropriate ratios for the preservation of the bacteria
present in the therapeutic composition. For example, the reduced
atmosphere may comprise 80% N2, 10% CO2 and 10% H2. In addition, or
alternatively, the method may comprise a step of lyophilising the
bacteria obtained in (i) and optionally (ii), optionally in the
presence of a stabiliser and/or cryprotectant. The method may also
comprise a step of preparing a capsule, tablet, or enema comprising
the bacteria obtained in (i) and optionally (ii). The capsule or
tablet may be enteric-coated, pH dependent, slow-release, and/or
gastro-resistant.
The composition of the invention may also be provided in the form
of a food supplement, beverage or other food stuff. The invention
thus also relates to a food product or a vaccine comprising a
composition of the invention.
Also provided is an immunogenic composition comprising fragments of
bacteria selected from the those listed in Table 1, for use as an
adjuvant to an anti-PD-1/PD-L1/PD-L2 antibody-based therapy
administered to a cancer patient.
Biomarker
The invention provides microbiome biomarkers that are predictive of
tumor response to therapy in a cancer patient with an immune
checkpoint inhibitor. In particular, the invention provides a
microbiome biomarker signature that is predictive of tumor response
therapy with an immune checkpoint inhibitor. As used herein, a
microbiome biomarker signature is a composite biomarker signature
that comprises bacteria from at least 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14 or 15 bacterial species as shown in Table 1 which
each have increased abundance in subjects that are responsive to
therapy with an immune checkpoint inhibitor. In one embodiment, the
signature comprises bacteria from at least 9, 10, 11, 12, 13, 14 or
15 bacterial species selected from Table 1 which each have
increased abundance in a population of subjects that are responsive
to therapy with an immune checkpoint inhibitor. The biomarker
signature is described in more detail below.
Another aspect provides a method of treating cancer in a subject
comprising administering a therapeutically effective amount of an
immune checkpoint inhibitor to said subject, wherein the subject
has been determined to have a favorable microbial profile in the
gut microbiome. A favorable microbial profile is characterised by
the presence of the biomarkers/biomarker signature described
herein.
Another aspect provides a method of treating cancer in a subject,
wherein the subject has been determined to have an unfavorable
microbial profile in the gut microbiome. A unfavorable microbial
profile is characterised by the absence of the biomarkers/biomarker
signature described herein. The method may further comprise
administration of an anti-cancer therapy that is not an immune
checkpoint inhibitor therapy. In another embodiment, the method
comprises administration of a therapeutic bacterial composition
described herein and co-therapy with an immune checkpoint inhibitor
therapy, e.g. a PD-1 inhibitor.
Thus, the invention also relates to a method for identifying a
subject that will respond to therapy with an immune checkpoint
inhibitor, e.g. PD-1, comprising determining the abundance of one
or more of the bacteria identified as B1, B2, B3, B4, B5, B6, B7,
B8, B9, B10, B11, B12, B13, B14 and/or B15 in Table 1 in a
biological sample from said subject that comprises gut (i.e.
intestinal) flora wherein an increase in the abundance of one or
more of B1, B2, B3, B4, B5, B8, B7, B8, B9, B10, B11, B12, B13, B14
and/or B15, e.g. one or more of B1, B2, B3, B4, B5, B8, B7, B8
and/or B9, is indicative that the subject will respond to therapy
with an immune checkpoint inhibitor, e.g. PD-1. B1 to B15 are
listed in Table 1 and this includes references to sequence
identifiers to define the bacteria. Corresponding sequences are
listed in Table 2. In one embodiment, the subject is a patient that
has been diagnosed with a cancer, e.g. melanoma.
In particular, the invention also relates to a method for
predicting a response to an immune checkpoint inhibitor therapy in
a subject having cancer/a method for identifying a subject that
will respond to therapy with an immune checkpoint inhibitor, the
method comprising:
a) determining the abundance of one or more of the bacteria
selected from B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12,
B13, B14 and/or B15 in Table 1 in a biological sample obtained from
the subject and
b) comparing the abundance to a reference level from cancer
patients that do not respond to therapy with an immune checkpoint
inhibitor; or comparing the abundance to a reference level from
cancer patients that respond to therapy with an immune checkpoint
inhibitor;
wherein if the reference level is from cancer patients that do not
respond to therapy with an immune checkpoint inhibitor, then an
increase in the abundance of one or more of B1, B2, B3, B4, B5, B6,
B7, B8, B9, B10, B11, B12, B13, B14 and/or B15 compared to the
reference level, is indicative that the subject will respond to
therapy with an immune checkpoint inhibitor or
wherein if the reference level is from patients that do respond to
therapy with an immune checkpoint inhibitor, then the same,
substantially the same or an increase in the abundance of one or
more of B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14
and/or B15, is indicative that the subject will respond to therapy
with an immune checkpoint inhibitor.
An additional step may include identifying the subject that will
respond to therapy.
In particular, the invention also relates to a method for
predicting a response to an immune checkpoint inhibitor therapy in
a subject having cancer/a method for identifying a subject that
will respond to therapy with an immune checkpoint inhibitor, the
method comprising:
a) determining the abundance of one or more of the bacteria
selected from B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11, B12,
B13, B14 and/or B15 in Table 1 in a biological sample obtained from
the subject and;
b) comparing the abundance to a reference level from cancer
patients or healthy subjects and
c) applying random forest analysis. In this embodiment, the
reference level is from cancer patients, that is a pool of cancer
patients. These may include responders and non-responders.
An additional step may include identifying the subject that will
respond to therapy or prediction a response.
Thus, the abundance of bacteria from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14 or 15 different species selected from B1, B2, B3,
B4, B5, B6, B7, B8, B9, B10, B11, B12, B13, B14 and B15 in Table 1
is determined. Respective sequences characterising the species are
provided as SEQ IDs 1 to 15. As explained elsewhere, SEQ IDs 16-29
can also be used. In some embodiments, the abundance of bacteria
selected from at least 9, 10, 11, 12, 13, 14 or 15 different
species identified as B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11,
B12, B13, B14 and B15 in Table 1 is determined. Thus, the abundance
of bacteria having sequences IDs selected from at least 9 of the
following SEQ IDs is determined: SEQ ID NO. 1, 2, 3, 4, 5, 6, 7, 8,
9, 10, 11, 12, 13, 14 or 15 or sequences with at least 97%, 98%,
98.7% or 99% sequence identity thereto, such as, for example SEQ
IDs 16 to 29.
Also provided is a method for predicting relapse in a patient who
is treated or who has been treated for a cancer, comprising
assessing, in faeces samples from said patient obtained e.g. at
different time-points, the presence/relative abundance of one or
more bacteria selected from B1, B2, B3, B4, B5, B6, B7, B8, B9,
B10, B11, B12, B13, B14 and/or B15.
When abundance is determined, an abundance score is obtained for
each of the bacteria, i.e. bacterial species, and measured.
According to the method, an increase in the abundance, i.e. the
abundance score, of one or more of the bacteria listed in Table 1
is indicative that the subject will respond to therapy with an
immune checkpoint inhibitor. An increase refers to an increase of
abundance, i.e. the abundance score, compared to a reference value.
Therefore, the method may also comprise comparing the abundance one
or more of the bacteria listed in Table 1 to one or more reference
value. For example, the abundance of one or more of the bacteria
listed in Table 1 can be compared to a reference value for one or
more of the bacteria listed in Table 1. Alternatively, the
arithmetic mean of the abundance of one or more of the bacteria
listed in Table 1 can be compared to a single reference value which
is the reference arithmetic mean of the abundance of one or more of
the bacteria listed in Table 1. In one embodiment, the method
determines the abundance of at least 9, 10, 11, 12, 13, 14 or 15
different bacteria selected from B1 to B15, thus determining a
microbiome biomarker signature, i.e. a microbiome biomarker
signature score, that is based on the composite signature.
In one embodiment of the methods, the abundance of all of the
bacteria listed in Table 1 is determined. In another embodiment,
the abundance of a subset the bacteria listed in Table 1 is
determined. For example, the subset comprises or consists of 1, 2,
3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 different bacteria
selected from Table 1. In one embodiment, the subset comprises or
consists of 9 bacteria, e.g. Eisenbergiella sp., Butyricicoccus
sp., Clostridiales sp., Alistipes obesi, Alistipes indistinctus,
Gordonibacter urolithinfaciens, Faecalitalea sp., Blauti sp. (B8),
and Barnesiella intestinihominis. In one embodiment, the subset
comprises or consists of 9 or 12 bacteria, e.g. one of the
bacterial consortia in Table 3. In one embodiment, the biomarker
does not comprise an Alistipes species.
The reference value may be a predetermined value from a reference
sample. For example, the reference value can be the average
abundance of each of the bacteria or their composite signature,
respectively, in a pool of reference subjects.
For example, the reference value is a predetermined value, e.g. a
predetermined threshold value. Such a value can be predetermined
from a reference sample. A predetermined threshold value relating
to abundance of one or more bacteria of B1 to B15 refers to the
abundance of the bacteria in the sample as a proportion of the
total microbiota in the sample, for example a stool sample, above
or below which the sample is scored as being positive for the
signature and thus responsive to therapy with an immune checkpoint
inhibitor. For example, if the abundance score for the test sample
is at or above a predetermined threshold, then the sample is
considered to be positive for the signature and the subject is
responsive to therapy with an immune checkpoint inhibitor.
For example, abundance scores of the tested bacteria levels in a
sample pool are stored on a computer, or on computer-readable
media, to be used as reference levels in comparisons to the
abundance of the tested bacteria from the test sample when needed.
Machine learning algorithms and/or models commonly used in the
identification of biomarkers, such as a Cox model, trained using
training data comprising information on a plurality of biomarkers
in a set of subjects or other models may be used to establish
reference values and or to correlate abundance of the bacteria
selected from one or more of the bacteria listed in Table 1 in the
sample with the subject's responsiveness to treatment with an
immune checkpoint inhibitor.
The term "correlating" is used herein to determine or calculate
responsiveness to treatment status based on modulated abundance of
one or more bacteria should be understood to mean any methods of
correlation, e.g. algorithmic methods. The methodology described
herein employs a mathematical modelling technique known as Random
Forest Classification, but other modelling techniques may be
employed. Therefore, in one embodiment, a Random Forest
Classification Model or similar model is used to correlate
abundance of the bacteria selected from one or more of the bacteria
listed in Table 1 in the sample with the subject's responsiveness
to treatment with an immune checkpoint inhibitor. Thus, in one
embodiment, the methods of the invention may employ a computer
program to correlate modulated abundance of the bacteria with
immune checkpoint inhibitor treatment response.
Alternatively, the reference value is not predetermined, but it is
established as part of a single experiment. Thus, the abundance of
the one or more tested bacteria in the test sample may be compared
to the abundance of the one or more tested bacteria in the pool of
samples, where abundance of the tested bacteria from the test
sample and abundance of the tested bacteria from the pool are
determined during the course of a single experiment.
In the various embodiments, the reference sample/sample pool may be
a population of cancer patients that have been shown to be
responsive or non-responsive to therapy with an immune checkpoint
inhibitor. In other embodiments, the reference sample/sample pool
may be a population of cancer patients that have not yet received
therapy with a checkpoint inhibitor.
In one embodiment, the reference sample used to establish a
reference value may be from non-responders to immune checkpoint
inhibitor therapy. If the test sample shows an increased abundance
of the one or more bacteria selected from B1 to B15 compared to the
reference sample, then the test subject is likely to respond to
therapy with a checkpoint immune inhibitor. The increase may be at
least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or more.
In one embodiment, the reference sample used to establish a
reference value may be from responders to immune checkpoint
inhibitor therapy. If the test sample shows the same, substantially
the same or an increase in the abundance of the one or more
bacteria selected from B1 to B15 than the reference sample, then
the test subject is likely to respond to therapy with a checkpoint
immune inhibitor.
As a skilled person would understand, a reference value or
reference gene signature score as used herein means the score for a
bacterial abundance signature that has been determined to divide at
least the majority of responders from at least the majority of
non-responders in a reference population of subjects.
As used herein, a "good responder to a treatment", also called a
"responder" or "responsive" patient or in other words a patient who
"benefits from" this treatment, refers to a patient who is affected
with a cancer and who shows or will show a clinically significant
relief in the cancer after receiving this treatment. Conversely, a
"bad responder" or "non-responder" is one who does not or will not
show a clinically significant relief in the cancer after receiving
this treatment. The response to treatment may be assessed according
to the standards recognized in the art, such as immune-related
response criteria (irRC), WHO or RECIST criteria.
A signature biomarker described herein is useful to identify cancer
patients who are most likely to achieve a clinical benefit from
treatment with an immune checkpoint inhibitor. This utility
supports the use of these biomarkers in a variety of research and
commercial applications. Including but not limited to, clinical
trials of PD-1 antagonists in which patients are selected on the
basis of their microbiome gene signature score, diagnostic methods
and products for determining a patients microbiome gene signature
score or for classifying a patient as positive or negative for a
microbiome signature biomarker, personalized treatment methods
which involve tailoring a patient's drug therapy based on the
patient's microbiome signature score, as well as pharmaceutical
compositions and drug products comprising a PD-1 antagonist for use
in treating patients who test positive for a microbiome signature
biomarker.
A skilled person would also understand that the utility of any of
the applications claimed herein does not require that 100% of the
patients who test positive for a biomarker of the invention achieve
an anti-tumor response to an immune checkpoint inhibitor, nor does
it require a diagnostic method or kit to have a specific degree of
specificity or sensitivity in determining the presence or absence
of a biomarker in every subject, nor does it require that a
diagnostic method claimed herein be 100% accurate in predicting for
every subject whether the subject is likely to have a beneficial
response to a PD-1 antagonist. Thus, the inventors herein intend
that the terms "determine", "determining" and "predicting" should
not be interpreted as requiring a definite or certain result;
instead these terms should be construed as meaning either that a
claimed method provides an accurate result for at least the
majority of subjects or that the result or prediction for any given
subject is more likely to be correct than incorrect. Preferably,
the accuracy of the result provided by a diagnostic method of the
invention is one that a skilled artisan or regulatory authority
would consider suitable for the particular application in which the
method is used.
As used herein, the sample is a biological sample from the gut,
i.e. one that comprises gut intestinal flora. This refers to a
sample obtained from the gut of a subject, for example a faecal
sample. Methods of isolating bacteria from a faecal sample are
known. In some cases, the microbiome sample is obtained by mucosal
biopsy. A test sample is sample obtained from a subject that is
being assessed.
In one embodiment of the method, the abundance is relative
abundance. As used herein, the term "relative abundance" as applied
to a bacterium in a sample should be understood to mean the
abundance of the bacterium in the sample as a proportion of the
total microbiota in the sample or a reference sample. In one
embodiment, the relative abundance is the abundance of the
bacterium in the sample as a proportion of the total microbiota in
the sample.
In one embodiment, the modulated abundance is a difference in
relative abundance of the bacterium in the sample compared with the
relative abundance in the same sample from a reference subject.
In one embodiment, the abundance of the bacterium in the sample as
a proportion of the total microbiota in the sample is measured to
determine the relative abundance of the bacterium. Then, in such
embodiments, the relative abundance of the bacterium in the sample
is compared with the relative abundance in the same sample from a
reference individual (also referred to herein as the "reference
relative abundance"). A difference in relative abundance of the
bacterium in the sample, e.g. an increase, compared to the
reference relative abundance is a modulated relative abundance.
Detection of modulated abundance can also be performed in an
absolute manner by comparing sample abundance values with absolute
reference values.
Any suitable method of detecting bacterial presence/abundance may
be employed, including, for example, agar plate quantification
assays, fluorimetric sample quantification, PCR methods, 16S
rRNA/rDNA gene amplicon sequencing, Shotgun metagenomic sequencing
and dye-based metabolite depletion or metabolite production assays.
The PCR technique used can quantitatively measure starting amounts
of DNA, cDNA, or RNA. Examples of PCR-based techniques according to
the invention include techniques such as, but not limited to,
quantitative PCR (Q-PCR), reverse-transcriptase polymerase chain
reaction (RT-PCR), quantitative reverse-transcriptase PCR
(QRT-PCR), rolling circle amplification (RCA) or digital PCR. These
techniques are well known and easily available and do not need a
precise description. In a particular embodiment, the determination
of the copy number of the bacterial genes of the invention is
performed by quantitative PCR.
In one embodiment, the sample is analysed using a nucleic acid
amplification reaction. Analysing may include detecting family,
order-, class- and/or genus-specific 16S rRNA/rDNA or other
sequences in the bacterial genome. In one embodiment, full length
16S rDNA may be detected. In one embodiment, partial 16S rDNA may
be detected, for example one of the V regions. In one embodiment,
analysing includes hybridizing bacterial nucleic acid in the sample
to beads or to an array, e.g. a nucleic acid microarray.
The PCR-based techniques are performed with amplification primers
designed to be specific for the sequences which are measured. The
present invention hence also pertains to a set of primers suitable
for performing the above method, i.e., a set of primers comprising
primer pairs for amplifying sequences specific for each of the
microorganism species to be detected (i.e., at least one more
species selected amongst those recited in Tables 1 and 2 and
3).
16S rDNA sequence is provided herein for B1-B15 and this can be
used to generate primers for such an analysis. In one embodiment, a
plurality of the bacteria is detected. In one embodiment, the
sample is analysed for nucleic acid of the bacteria using genome
sequencing.
In one embodiment, the subject is a cancer patient, such as
melanoma patient. The cancer patient may or may not have received
anti-cancer treatment. Thus, the subject may be one that is in need
of treatment with an immune checkpoint inhibitor. In one
embodiment, the subject is a healthy individual, for example a
healthy individual with a family history of cancer, such as
melanoma.
In one embodiment, if the subject is a cancer patient and has been
identified as a subject that will respond to therapy with an immune
checkpoint inhibitor, then the method may include the further step
of administering an immune checkpoint inhibitor to said
patient.
In one embodiment, the method also comprises the prior step of
obtaining the biological sample that comprises gut flora.
In one embodiment, the method also includes the initial step of
identifying a subject in need of treatment with the immune
checkpoint inhibitor.
In one embodiment of the methods, if the subject is identified as a
responder, e.g. If one or more of the bacteria listed in Table 1
has been shown to have an increased abundance in the sample, an
anti-cancer therapy comprising an immune checkpoint inhibitor is
administered to the subject.
Checkpoint inhibitors are as defined herein. In one embodiment of
the methods, the immune checkpoint inhibitor inhibits PD-1
activity, i.e. acts as a PD-1 antagonist. In one embodiment of the
methods, the immune checkpoint inhibitor inhibits PD-L1 activity,
i.e. acts as a PD-L1 antagonist. In one embodiment of the methods,
the immune checkpoint inhibitor inhibits CTLA-4 activity, i.e. acts
as a CTLA-4 antagonist. In one embodiment of the methods, the
immune checkpoint inhibitor inhibits LAG3, TIGIT or
TIM3-activity.
In one embodiment the immune checkpoint inhibitor is an anti PD-1,
PD-L1 or CTLA-4 antibody. In one embodiment, the anti PD-1 antibody
is selected from nivolumab, pembrolizumab, cemiplimab, avelumab,
durvalumab, atezolizumab, Spartalizumab, Camrelizumab, Sintilimab,
Tislelizumab, Pidilizumab or Toripalimab, Ipilimumab or
Tremelimumab.
In one embodiment, the immune checkpoint inhibitor is an
interfering nucleic acid molecule. In one embodiment, the
interfering nucleic acid molecule is an siRNA molecule, an shRNA
molecule or an antisense RNA molecule.
In one embodiment, the immune checkpoint inhibitor is a small
molecule or PROteolysis TArgeting Chimera (PROTAC) or another
immune checkpoint inhibitor as defined above.
In one embodiment, in a further step of the method, surgical,
radiation, and/or chemotherapeutic cancer intervention is carried
out or a second anti-cancer therapeutic is administered to said
subject.
In another aspect, the invention relates to a method of detecting
the risk that a subject will not respond to therapy with an immune
checkpoint inhibitor. The method comprising determining the
abundance of one or more of the bacteria listed in Table 1 in a
biological sample from said subject that comprises gut intestinal
flora wherein a decrease in the abundance or an abundance below a
reference level of one or more of the bacteria listed in Table 1 is
indicative that the subject will not respond to therapy with an
immune checkpoint inhibitor. The method may also comprise comparing
the abundance of one or more of the bacteria listed in Table 1 to
one or more reference value. A reference value is as described
above. The abundance that is determined is relative abundance. In a
further step, if the subject has been identified as a subject that
will not respond to therapy with an immune checkpoint inhibitor,
alternative anti-cancer treatment is administered. Alternatively,
in a further step, if the subject has been identified as a subject
that will not respond to therapy with an immune checkpoint
inhibitor, a therapeutic bacterial composition as described herein
is administered together with a checkpoint inhibitor therapy, e.g.
an anti PD-1 therapy.
In another aspect, the invention relates to a method of
discriminating between subjects that respond to therapy with an
immune checkpoint inhibitor and subjects that do not respond to
therapy with an immune checkpoint inhibitor. The method comprising
determining the abundance of one or more of the bacteria listed in
Table 1 in a biological sample from said subject that comprises gut
intestinal flora wherein a decrease in the abundance or a abundance
below a reference level of one or more of the bacteria listed in
Table 1 is indicative that the subject will not respond to therapy
with an immune checkpoint inhibitor and an increase in the
abundance of one or more of the bacteria listed in Table 1 is
indicative that the subject will respond to therapy with an immune
checkpoint inhibitor. The method may also comprise comparing the
abundance one or more of the bacteria listed in Table 1 to one or
more reference value. A reference value is as described above. The
abundance that is determined is relative abundance. In a further
step, if the subject has been identified as a subject that will not
respond to therapy with an immune checkpoint inhibitor, alternative
anti-cancer treatment is administered.
In one embodiment of the biomarker methods above, modulated
abundance of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14
or 15 different bacteria selected from Table 1 is indicative of a
response to treatment. In another embodiment of the biomarker
methods above, modulated abundance of at least 9, 10, 11, 12, 13,
14 or 15 different bacteria selected from Table 1 is indicative of
a response to treatment. Thus, establishing a composite signature
that includes abundance of at least 9, 10, 11, 12, 13, 14 or 15
different bacteria is a particular embodiment of the methods. It is
the totality of the bacteria, i.e. the biomarker signature, that
provides a particularly powerful discriminatory tool.
In one embodiment of the various methods above, the abundance of at
least 9 bacterial species/a population of 9 bacterial species
selected from those in Table 1 is assessed, i.e. 9 species selected
from SEQ ID Nos. 1, 2, 3, 4, 5 6, 7, 8, 9, 10, 11, 12, 13, 14 and
15. In one embodiment, the subset of 9 corresponds to a consortium
as shown in Table 3, i.e. consortia 2, 4, 5, 6 or 10. In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 1 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species comprise
bacteria as defined by SEQ ID NO. 2 or a sequence with at least
97%, 98%, 98.7% or 99% sequence identity thereto. =In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 3 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species comprises
bacteria as defined by SEQ ID NO. 4 or a sequence with at least
97%, 98%, 98.7% or 99% sequence identity thereto. In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 5 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species comprise
bacteria as defined by SEQ ID NO. 6 or a sequence with at least
97%, 98%, 98.7% or 99% sequence identity thereto. In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 7 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species comprise
bacteria as defined by SEQ ID NO. 8 or a sequence with at least
97%, 98%, 98.7% or 99% sequence identity thereto. In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 9 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species comprise
bacteria as defined by SEQ ID NO. 10 or a sequence with at least
97%, 98%, 98.7% or 99% sequence identity thereto. In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 11 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species comprise
bacteria as defined by SEQ ID NO. 12 or a sequence with at least
97%, 98%, 98.7% or 99% sequence identity thereto. In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 13 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species comprise
bacteria as defined by SEQ ID NO. 14 or a sequence with at least
97%, 98%, 98.7% or 99% sequence identity thereto. In one
embodiment, the 9 species comprise bacteria as defined by SEQ ID
NO. 15 or a sequence with at least 97%, 98%, 98.7% or 99% sequence
identity thereto. In one embodiment, the 9 species do not comprise
an Alistipes species.
In one embodiment, the biomarker methods above may comprise a
further step of determining another biomarker that is predictive of
tumor response with an immune checkpoint inhibitor, for example a
PD-1, PD-L1 or CTLA-4 antagonist. For example, the biomarker may be
a Programmed Death Ligand 1 (PD-L1) or Programmed Death Ligand 1
(PD-L2) gene signature. Thus, the method may comprise the step of
obtaining a sample from the tumor of a test subject, measuring RNA
expression level in the tumor sample of one or more gene in a PD-1
and/or PD-L1 gene signature and comparing the RNA expression level
to a reference level. Expression can be measured by any appropriate
methods, including immunohistochemistry.
In another aspect, the invention relates to one or more of the
bacteria listed in Table 1 for use as a predictive biomarker in
determining the efficacy of therapeutic intervention with
checkpoint inhibitor, e.g. PD-1 therapy. The term predictive
biomarker as used herein is to describe a biomarker that gives
information about the effect of a therapeutic intervention, i.e.
responsiveness to treatment with an immune checkpoint inhibitor.
Thus, the invention also relates to the use of one or more
bacterium: e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15
different bacteria selected from one or more of the bacterial
species listed in Table 1 in identifying a patient that will
respond to therapy with an immune checkpoint inhibitor.
The invention also relates to a biomarker signature, that is a
consortium of one or more of the bacteria listed in Table 1, e.g.
as in Table 3, which can be used to predict the efficacy of
therapeutic intervention with checkpoint inhibitor therapy, e.g.
with a PD-1 inhibitor or with another checkpoint inhibitor
therapy.
Systems and Computer Readable Media
Embodiments of the invention also provide for systems (and computer
readable media for causing computer systems) to perform a method
for determining responsiveness to treatment with an immune
checkpoint inhibitor in a subject. In another aspect, a
computer-implemented method is provided for indicating a likelihood
that a subject responds to treatment with an immune checkpoint
inhibitor. The method comprises: retrieving on a computer biomarker
information for an individual, wherein the biomarker information
comprises biomarker values that each correspond to the abundance of
one or more bacteria selected from the group of bacteria set forth
in Table 1; performing with the computer a classification of each
of the biomarker values; and indicating a likelihood that the
subject responds to treatment with an immune checkpoint inhibitor
based upon a plurality of classifications.
In another aspect, a computer program product is provided for
indicating a likelihood that a subject responds to treatment with
an immune checkpoint inhibitor. The computer program product
includes a computer readable medium embodying program code
executable by a processor of a computing device or system, the
program code comprising: code that retrieves data attributed to a
biological sample from an individual, wherein the data comprises
biomarker values that each correspond to the abundance of one or
more bacteria selected from the group of bacteria set forth in
Table 1; and code that executes a classification method that
indicates a likelihood that the individual responds to treatment
with an immune checkpoint inhibitor as a function of the biomarker
values.
In one embodiment the reference data stored in the storage device
to be read by the comparison module is compared, e.g., relative
abundance of a particular bacterium in a reference sample as
described herein. The "comparison module" can use a variety of
available software programs and formats for the comparison
operative to compare bacteria abundance information data determined
in the determination system to reference samples and/or stored
reference data, e.g. a predetermined threshold value. In one
embodiment, the comparison module is configured to use pattern
recognition techniques to compare information from one or more
entries to one or more reference data patterns. The comparison
module may be configured using existing commercially-available or
freely-available software for comparing patterns and may be
optimized for particular data comparisons that are conducted. The
comparison module provides computer readable information related to
the response-associated bacteria.
The comparison module provides a computer readable comparison
result that can be processed in computer readable form by
predefined criteria, or criteria defined by a user, to provide a
content based in part on the comparison result that may be stored
and output.
The methods described herein therefore provide for systems (and
computer readable media for causing computer systems) to perform
methods for determining responsiveness to treatment with an immune
checkpoint inhibitor in a subject.
FMT
Implantation or administration of human microbiota into the bowel
of a sick patient is called Faecal Microbiota Transplantation
(FMT), also commonly known as faecal bacteriotherapy. FMT is
believed to repopulate the gut with a diverse array of microbes
that bring missing beneficial functions or microbiota to the
resident gut bacteria, displace harmful microbiota or control key
pathogens by creating an unfavourable ecological environment.
In another aspect, the invention relates to a method for
screening/identifying a faecal donor comprising assessing a faecal
sample of a subject for the presence of one or more bacteria
associated with response to cancer; e.g. response to cancer when a
patient is treated with an immune checkpoint inhibitor and
identifying the faecal donor based on the presence and/or abundance
of one or more bacteria.
For example, in such a method, the one or more bacteria selected
from Table 1 and the faecal donor is identified based on the
presence and/or abundance of one or more bacteria selected from
Table 1.
In another aspect, the invention relates to a method for
screening/identifying a faecal donor comprising assessing a faecal
sample of a subject for the presence of one or more bacteria
selected from Table 1 and identifying the faecal donor based on the
presence and/or abundance of one or more bacteria selected from
Table 1. The method may also comprise obtaining a faecal sample
from a donor. Assessing a faecal sample of a subject for the
presence of one or more bacteria can be done by methods known in
the art, e.g. sequence analysis of bacterial genomes, e.g. using a
shotgun sequencing approach. For example, one or more of the
bacteria is present above a predetermined threshold, the donor is
selected as a donor for bacteriotherapy purposes. The predetermined
threshold may be based on the average abundance of the one or more
bacteria in faecal samples obtained from a donor population. A
higher than average abundance indicates that the faeces are
suitable for FMT therapy.
The invention also relates to a use of one or more bacteria
selected from Table 1 in a method for identifying a donor for FMT
therapy.
The invention relates to a method for treating a faecal transplant
prior to administration to a subject comprising supplementing the
faecal transplant with one or more bacterial isolates selected from
Table 1 or with a faecal sample obtained from a donor by the method
described above.
According to another aspect of the present invention, an individual
in need of a treatment with an immune checkpoint inhibitor therapy
is treated by FMT, using faecal microbiota from healthy
individual(s) that has been shown to be abundant in one or more of
the species in table 1, and/or faecal microbiota from one or
several individual(s) treated with an immune checkpoint inhibitor
therapy and who proved to respond to this therapy, and/or faecal
microbiota from one or several individual(s) exhibiting a gut
microbiota profile that identifies him/her/them as likely to
respond to the envisioned treatment or from a responding
patient.
In the aspects above, the FMT therapy is for the treatment of a
disease as mentioned herein, e.g. a cancer such as melanoma.
Composition and Methods for Increasing Abundance of Bacteria in a
Host
In another aspect of the invention, a subject's microbiome may be
altered to increase the abundance of bacteria listed in Table 1 or
a subset thereof. Glycan metabolism has been shown to influence the
human gut microbiota and prebiotics can enrich bacterial taxa that
promote anti-tumor immunity (Koropatkin et al, Nature Reviews
Microbiology volume 10, pages 323-335 (2012); Li et al, Cell
Report, Volume 30. ISSUE 6, P1753-1766.e6, Feb. 11, 2020). Thus,
there is provided a method for increasing the abundance of bacteria
listed in table 1 in a subject or a subset thereof by
administration of a composition comprising oligosaccharides, such
as glycans. Compositions comprising oligosaccharides, such as
glycans for use in such a method are also envisaged.
Kits
In a further aspect, the invention relates to a kit. The kit
includes a composition described herein and optionally an
anti-cancer treatment that includes an immune checkpoint inhibitor
as described herein. In an example, the kit can include materials
to ship the collected material without harming the samples (e.g.,
packaged in lyophilized form, or packaged in an aqueous medium
etc.). The kit may include the processed material or treatment in a
sterile container, such as a nasogastric (NG) tube, a vial (e.g.,
for use with a retention enema), a gastro-resistant capsule (e.g.,
acid-bio resistant to reach the intestinal tract, having a sterile
outside), etc. The kit may also comprise instructions for use.
In an alternative aspect, the kit comprises a sealable container
configured to receive a biological sample, such as a faecal sample;
polynucleotide primers for amplifying a 16S rDNA polynucleotide
sequence from at least one gut associated bacterium to form an
amplified 16S rDNA polynucleotide sequence, wherein the amplified
16S rDNA sequence has at least 97%, 98%, 98.7% or 99% homology to a
polynucleotide sequence selected from SEQ ID NOs 1 to SEQ ID NO 15,
e.g. SEQ ID NOs 16 to 29; a detecting reagent to detect the
amplified 16S rDNA sequence; and instructions for use.
The invention also relates to as kit comprising a composition
comprising oligosaccharides, such as glycans for use in a method
for increasing the abundance of bacteria listed in table 1 in a
subject or a subset thereof by administration of the
composition.
The invention also relates to the use of a composition of the
invention, i.e. comprising or consisting of one or more a bacterial
isolate as shown in Table 1 with reference to a SEQ ID NO. shown
therein, in increasing efficacy of an anti-cancer treatment with an
immune checkpoint inhibitor. The invention also relates to the use
of a composition of the invention, i.e. comprising or consisting of
one or more a bacterial isolate as shown in Table 1 with reference
to a SEQ ID NO. as shown in the Table, in enhancing immune
checkpoint blockade. The invention also relates to a method for
increasing efficacy of an anti-cancer treatment with an immune
checkpoint inhibitor comprising administering a composition of the
invention, i.e. comprising or consisting of one or more bacterial
isolate as shown in Table 1 with reference to a SEQ ID NO., to a
subject. The invention also relates to a method for enhancing
immune checkpoint blockade comprising administration of a
composition of the invention, i.e. comprising or consisting of one
or more bacterial isolate as shown in Table 1 with reference to a
SEQ ID NO. as shown in the Table to a subject.
The invention also relates to the use of a composition of the
invention in providing an immunostimulatory effect.
The invention also relates to a method for determining if a cancer
patient needs a bacterial composition of the invention, i.e.
comprising or consisting of one or more a bacterial isolate as
shown in Table 1 with reference to a SEQ ID NO. as shown therein,
before administration of an immune checkpoint inhibitor comprising
assessing, in a faeces sample from said patient, the presence or
absence or one or more bacterial isolates selected from the species
in Table 1.
Aspects
The invention is further described in the following aspects. 1. A
composition comprising isolated bacteria selected from at least two
species wherein the bacteria from the first species comprise a 16S
rDNA sequence having at least 98.7% sequence identity with a
nucleic acid sequence according to SEQ ID NO: 1, and the bacteria
from the second species comprise a 16S rDNA sequence having at
least 98.7% sequence identity with a nucleic acid sequence
according to SEQ ID NO: 2. 2. The composition according to aspect
1, further comprising isolated bacteria from at least 1, 2, 3, 4,
5, 6, 7, 8, 9, 10, 11, 12 or 13 different species wherein the
bacteria comprise a 16S rDNA sequence selected from a sequence
having at least 98.7% sequence identity with a nucleic acid
sequence according to SEQ ID NO: 3 to 15. 3. The composition
according to aspect 1 further comprising isolated bacteria from at
least 4 different species wherein the bacteria comprise a 16S rDNA
sequence selected from a sequence having at least 98.7% sequence
identity with a nucleic acid sequence according to SEQ ID NO: 3 to
15. 4. The composition according to aspect 1, further comprising
isolated bacteria from at least 7 different species wherein the
bacteria comprise a 16S rDNA sequence selected from a sequence
having at least 98.7% sequence identity with a nucleic acid
sequence according to SEQ ID NO: 3 to 15. 5. The composition
according to aspect 1, further comprising a bacterial isolate
comprising a 168S rDNA sequence selected from a sequence having at
least 98.7% sequence identity with a nucleic acid sequence
according to SEQ ID NO: 7. 6. The composition according to aspect 1
comprising a consortium selected from consortia 1 to 4 or 6 to 10
as shown in Table 3. 7. The composition according to any preceding
aspect, wherein said composition is formulated for oral or rectal
administration. 8. The composition according to aspect 7, wherein
said composition is in the form of a capsule, tablet, gel or
liquid. 9. The composition according to aspect 8, wherein said
composition is encapsulated in an enteric coating. 10. The
composition according to any preceding aspect, wherein the
composition comprises live, attenuated or killed bacteria. 11. The
composition according to any preceding aspect, wherein the
composition comprises bacterial spores. 12. The composition
according to any of aspects 1 to 11, wherein the composition does
not comprise bacterial spores. 13. The composition according to any
preceding aspect, wherein the composition comprises bacterial
strains that originate from one or more human donor. 14. The
composition according to any preceding aspect, wherein the bacteria
are lyophilized. 15. The composition according to any preceding
aspect, wherein the composition comprises at least about
1.times.10.sup.3 to 1.times.10.sup.13 CFU of bacteria. 16. The
composition according to any preceding aspect, wherein
administration of the composition induces an immune response in a
subject and/or increases the efficacy of an anti cancer therapy
that includes an immune checkpoint inhibitor. 17. A pharmaceutical
composition comprising a composition of any of aspects 1 to 16 and
a pharmaceutical carrier. 18. The pharmaceutical composition
according to aspect 17, further comprising an effective amount of
an immune checkpoint inhibitor or a vaccine. 19. The pharmaceutical
composition according to aspect 18, wherein the immune checkpoint
inhibitor inhibits PD-1, PDL-1, CTLA-4, LAG3 or TIM-3 activity. 20.
The pharmaceutical composition according to aspect 19 wherein the
immune checkpoint inhibitor is an anti PD-1, PDL-1 or CTLA-4
antibody or fragment thereof. 21. The pharmaceutical composition
according to aspect 20 wherein the anti PD-1, PDL-1 or CTLA4
antibody is selected from nivolumab, pembrolizumab, cemiplimab,
avelumab, durvalumab, atezolizumab, spartalizumab, camrelizumab,
sintilimab, tislelizumab, pidilizumab toripalimab, Ipilimumab or
Tremelimumab. 22. The pharmaceutical composition according to
aspect 18, wherein the immune checkpoint inhibitor is an
interfering nucleic acid molecule, a small molecule or PROteolysis
TArgeting Chimera (PROTAC), alternative protein scaffold or other
immune checkpoint inhibitor. 23. The pharmaceutical composition
according to aspect 22, wherein the interfering nucleic acid
molecule is an siRNA molecule, an shRNA molecule or an antisense
RNA molecule. 24. A composition according to any of aspects 1 to
16, or a pharmaceutical composition of any of aspects 17 to 23 for
use in the treatment of disease. 25. A composition according to any
of aspects 1 to 16, or a pharmaceutical composition of any of
aspects 17 to 23 for use in the treatment of cancer or an
infectious disease or for use as a vaccine adjuvant or for
increasing the efficacy of a cancer treatment. 26. A method for
treating cancer or an infectious disease in a subject in need
thereof, comprising administering a composition according to any of
aspects 1 to 17 or a pharmaceutical composition of aspect 17, to
said subject. 27. The method of aspect 26 wherein said subject is
receiving, has received or will receive therapy with an immune
checkpoint inhibitor, thereby treating the cancer or infectious
disease. 28. A method for treating cancer in a subject in need
thereof comprising administering a composition according to aspect
18 to said subject. 29. The method according to aspect 26 or 27,
wherein administration of the composition enhances an immune
response by the subject and/or inhibits immune evasion by the
cancer and/or increases efficacy of an anti cancer treatment with
an immune checkpoint inhibitor. 30. The composition for use
according to aspect 25, or the method according to any of aspects
26 to 29 wherein the cancer is selected from melanoma melanoma,
such as Harding-Passey melanoma, juvenile melanoma, lentigo maligna
melanoma, malignant melanoma, acral-lentiginous melanoma,
amelanotic melanoma, benign juvenile melanoma, Cloudman's melanoma,
S91 melanoma, nodular melanoma, subungual melanoma, Cutaneous
melanoma, uveal/intraocular melanoma and superficial spreading
melanoma or bone cancer, pancreatic cancer, skin cancer, cancer of
the head or neck, cutaneous or intraocular malignant melanoma,
uterine cancer, ovarian cancer, rectal cancer, cancer of the anal
region, stomach cancer, testicular cancer, breast cancer, brain
cancer, carcinoma of the fallopian tubes, carcinoma of the
endometrium, carcinoma of the cervix, carcinoma of the vagina,
carcinoma of the vulva, cancer of the esophagus, cancer of the
small intestine, cancer of the endocrine system, cancer of the
thyroid gland, cancer of the parathyroid gland, cancer of the
adrenal gland, kidney cancer, sarcoma of soft tissue, cancer of the
urethra, cancer of the bladder, renal cancer, lung cancer,
non-small cell lung cancer, thymoma, urothelial carcinoma leukemia,
prostate cancer, mesothelioma, adrenocortical carcinoma, lymphomas,
such as such as Hodgkin's disease, non-Hodgkin's, gastric cancer,
and multiple myelomas. 31. The composition for use according to
aspect 25 or the method according to any of aspects 26 to 29,
wherein the composition or pharmaceutical composition is
administered by oral administration or rectal administration. 32.
The composition for use according to aspect 25 or the method
according to any of aspects 26 to 29, wherein said subject has
received prior anti cancer therapy with an immune checkpoint
inhibitor. 33. The composition for use according to aspect 25 or
the method according to any of aspects 26 or 29 further comprising
administering an anti cancer therapy with an immune checkpoint
inhibitor. 34. The composition for use or method according to
aspect 33, wherein the immune checkpoint inhibitor is administered
before, after or at the same time as the bacterial formulation. 35.
The composition for use or method according to aspect 33 or 34,
wherein the immune checkpoint inhibitor is administered by
injection. 36. The composition for use or method according to any
of aspects 33 to 35, wherein the injection is an intravenous,
intramuscular, intratumoural or subcutaneous injection. 37. The
composition for use or method according to any of aspects 33 to 36
wherein the immune checkpoint inhibitor inhibits PD-1, PDL-1 or
CTLA-4 activity. 38. The composition for use or method according to
aspect 37, wherein the immune checkpoint inhibitor is an anti PD-1,
PDL-1 or CTLA-4 antibody. 39. The composition for use method
according to aspect 38, wherein the anti PD-1. PDL-1 or CTLA4
antibody is selected from nivolumab, pembrolizumab, cemiplimab,
avelumab, durvalumab, atezolizumab, Spartalizumab, Camrelizumab,
Sintilimab, Tislelizumab, Pidilizumab, Toripalimab, Ipilimumab or
Tremelimumab. 40. The composition for use or method according to
any of aspects 33 to 37, wherein the immune checkpoint inhibitor is
an interfering nucleic acid molecule, a small molecule or
PROteolysis TArgeting Chimera (PROTAC) or other immune checkpoint
inhibitor. 41. The composition for use or method according to
aspect 40, wherein the interfering nucleic acid molecule is an
siRNA molecule, an shRNA molecule or an antisense RNA molecule or a
small molecule or peptide. 42. The composition for use according to
aspect 25 or 30 to 41, or the method according to any of aspects 26
to 41, further comprising surgical, radiation, and/or
chemotherapeutic cancer intervention or administration of a second
anti cancer therapeutic. 43. The composition for according to
aspect 25 or 30 to 42 or method according to any of aspects 26 to
42, further comprising administering to the subject an antibiotic.
44. The composition for use according to aspect 25 or 30 to 43 or
method according to any of aspects 26 to 43, wherein the subject is
identified as at risk of developing a cancer. 45. A kit comprising
a composition according to any of aspects 1 to 17, and optionally
an anti cancer treatment that includes an immune checkpoint
inhibitor. 46. A food product or a vaccine adjuvant comprising the
composition of any of aspects 1 to 17. 47. A method for treating
faecal transplant prior to administration to a subject comprising
supplementing the faecal transplant with isolated bacteria selected
from at least two species wherein the bacteria from the first
species comprise a 16S rDNA sequence having at least 98.7% sequence
identity with a nucleic acid sequence according to SEQ ID NO: 1,
and the bacteria from the second species comprise a 16S rDNA
sequence having at least 98.7% sequence identity with a nucleic
acid sequence according to SEQ ID NO: 2. 48. A use of a composition
of any of aspects 1 to 17 or a pharmaceutical composition of aspect
18, in increasing efficacy of an anti cancer treatment with an
immune checkpoint inhibitor. 49. A use of a composition of any of
aspects 1 to 17 or a pharmaceutical composition of aspect 18, in
enhancing immune checkpoint blockade. 50. A method for enhancing
immune checkpoint blockade comprising administering a composition
of any of aspects 1 to 17 or a pharmaceutical composition of aspect
18. 51. A composition comprising a bacterium selected from one or
more bacteria selected from Table 1. 52. A method for treating or
preventing cancer comprising modulating the level of one or more
bacteria selected from those of Table 1 in a subject.
The invention is also further described in the following additional
aspects. 1. A method for identifying a subject that will respond to
therapy with an immune checkpoint inhibitor comprising determining
the abundance of bacteria from at least 9 different species in a
biological sample from said subject that comprises gut flora
wherein said bacteria comprise a 16S rDNA sequence selected from
SEQ ID NOs: 1 to 15 or a sequence having at least 98.7% sequence
identity with a nucleic acid sequence selected from SEQ ID NOs: 1
to 15 wherein said abundance is indicative of a response of a
subject to therapy with an immune checkpoint inhibitor. 2. The
method for identifying a subject that will respond to therapy with
an immune checkpoint inhibitor according to aspect 1, the method
comprising: a) determining the abundance of the bacteria in a
biological sample obtained from the subject and b) comparing the
abundance to a reference level from cancer patients that do not
respond to therapy with an immune checkpoint inhibitor or cancer
patients that respond to therapy with an immune checkpoint
inhibitor; wherein if the reference level is from patients that do
not respond to therapy with an immune checkpoint inhibitor, then an
increase in the abundance of each of the bacteria compared to the
reference level, is indicative that the subject will respond to
therapy with an immune checkpoint inhibitor or wherein if the
reference level is from patients that do respond to therapy with an
immune checkpoint inhibitor, then the same or substantially the
same or an increase in abundance of each of the bacteria, is
indicative that the subject will respond to therapy with an immune
checkpoint inhibitor. 3. The method for identifying a subject that
will respond to therapy with an immune checkpoint inhibitor
according to aspect 1, the method comprising: a) determining the
abundance of the bacteria in a biological sample obtained from the
subject; b) comparing the abundance to a reference level from
cancer patients and c) applying random forest analysis. 4. The
method according to a preceding aspect, wherein the bacterial
species comprise a 16S rDNA sequence selected from SEQ ID NO: 1 or
2 or a 16S rDNA sequence having at least 98.7% sequence identity
thereto. 5. The method according to a preceding aspect, wherein the
method comprises determining the abundance of bacteria from 10, 11,
12, 13, 14 or 15 species wherein said bacteria comprise a 16S rDNA
sequence selected from SEQ ID NOs: 1 to 15 or a sequence having at
least 98.7% sequence identity with a nucleic acid sequence selected
from SEQ ID NOs: 1 to 15. 6. The method according to a preceding
aspect wherein said subject is a cancer patient. 7. The method
according to aspect 6, wherein the cancer is selected from
melanoma, bone cancer, pancreatic cancer, cancer of the head or
neck, cutaneous or intraocular malignant melanoma, uterine cancer,
ovarian cancer, rectal cancer, cancer of the anal region, stomach
cancer, testicular cancer, breast cancer, brain cancer, carcinoma
of the fallopian tubes, carcinoma of the endometrium, carcinoma of
the cervix, carcinoma of the vagina, carcinoma of the vulva, cancer
of the esophagus, cancer of the small intestine, cancer of the
endocrine system, cancer of the thyroid gland, cancer of the
parathyroid gland, cancer of the adrenal gland, kidney cancer,
sarcoma of soft tissue, cancer of the urethra, cancer of the
bladder, renal cancer, lung cancer, non-small cell lung cancer,
thymoma, urothelial carcinoma leukemia, prostate cancer,
mesothelioma, adrenocortical carcinoma, lymphomas, such as such as
Hodgkin's disease, non-Hodgkin's, gastric cancer, and multiple
myelomas. 8. The method according to aspect 7, wherein the melanoma
is selected from Harding-Passey melanoma, juvenile melanoma,
lentigo maligna melanoma, malignant melanoma, acral-lentiginous
melanoma, amelanotic melanoma, benign juvenile melanoma, Cloudman's
melanoma, S91 melanoma, nodular melanoma, subungual melanoma,
Cutaneous melanoma, uveal/intraocular melanoma and superficial
spreading melanoma. 9. The method according to a preceding aspect,
further comprising the step of identifying a subject in need of
treatment with the immune checkpoint inhibitor. 10. The method
according to a preceding aspect, further comprising administering
an immune checkpoint inhibitor to said subject. 11. The method
according to a preceding aspect wherein the immune checkpoint
inhibitor inhibits PD-1, PD-L1 or CTLA-4 activity. 12. The method
according to aspect 11, wherein the immune checkpoint inhibitor is
an anti PD-1, PDL-1 or CTLA-4 antibody. 13. The method according to
aspect 12, wherein the anti PD-1, PDL-1 or CTLA-4 antibody is
selected from nivolumab, pembrolizumab, cemiplimab, avelumab,
durvalumab, atezolizumab, Spartalizumab, Camrelizumab, Sintilimab,
Tislelizumab, Pidilizumab, Toripalimab, Ipilimumab or Tremelimumab.
14. The method according to any of aspects 1 to 11, wherein the
immune checkpoint inhibitor is an interfering nucleic acid
molecule, a small molecule or a PROteolysis TArgeting Chimera
(PROTAC) or other immune checkpoint inhibitor. 15. The method
according to aspect 14, wherein the interfering nucleic acid
molecule is an siRNA molecule, an shRNA molecule or an antisense
RNA molecule or a small molecule or peptide. 18. The method
according to a preceding aspect, wherein the abundance is the
abundance of the bacteria in the sample as a proportion of the
total microbiota in the sample. 17. The method according to a
preceding aspect, further comprising the step of obtaining a
biological sample that comprises gut flora from said subject. 18.
The method according to a preceding aspect, wherein the sample is a
faecal sample. 19. Use of bacteria selected from at least 9
different bacterial species wherein said bacteria comprise a 18S
rDNA sequence selected from SEQ ID NOs: 1 to 15 or a sequence
having at least 98.7% sequence identity with a nucleic acid
sequence selected from SEQ ID NOs: 1 to 15 in identifying a patient
that will respond to therapy with an immune checkpoint inhibitor.
20. A kit comprising a sealable container configured to receive a
biological sample; polynucleotide primers for amplifying a 18S rDNA
polynucleotide sequence from at least 9 different bacterial species
wherein said bacteria comprise a 18S rDNA sequence selected from
SEQ ID NOs: 1 to 15 or a sequence having at least 98.7% sequence
identity with a nucleic acid sequence selected from SEQ ID NOs: 1
to 15; a detecting reagent to detect the amplified 16S rDNA
sequence; and instructions for use. 21. A method for identifying a
faecal donor comprising assessing a faecal sample of a subject for
the presence of bacteria from at least 9 different bacterial
species wherein said bacteria comprise a 16S rDNA sequence selected
from SEQ ID NOs: 1 to 15 or a sequence having at least 98.7%
sequence identity with a nucleic acid sequence selected from SEQ ID
NOs: 1 to 15 and identifying the faecal donor based on the presence
and/or abundance of the bacteria. 22. The use of bacteria from at
least 9 different bacterial species wherein said bacteria comprise
a 16S rDNA sequence selected from SEQ ID NOs: 1 to 15 or a sequence
having at least 98.7% sequence identity with a nucleic acid
sequence selected from SEQ ID NOs: 1 to 15 in a method for
identifying a donor for FMT therapy. 23. A method for determining
if a cancer patient needs a bacterial compensation before
administration of an immune checkpoint inhibitor comprising
assessing, in a faeces sample from said patient, the presence or
absence of bacteria from at least 9 different bacterial species
wherein said bacteria comprise a 16S rDNA sequence selected from
SEQ ID NOs: 1 to 15 or a sequence having at least 98.7% sequence
identity with a nucleic acid sequence selected from SEQ ID NOs: 1
to 15. 24. A method for predicting a response to an immune
checkpoint inhibitor therapy in a subject having cancer comprising
determining the abundance of bacteria from at least 9 different
species wherein said bacteria comprise a 16S rDNA sequence selected
from SEQ ID NOs: 1 to 15 or a sequence having at least 98.7%
sequence identity with a nucleic acid sequence selected from SEQ ID
NOs: 1 to 15 in a biological sample from said subject that
comprises gut flora wherein said abundance is indicative of a
response or non-response of a subject to therapy with an immune
checkpoint inhibitor. 25. A method for predicting a response to an
immune checkpoint inhibitor therapy in a subject having cancer
according to aspect 24, the method comprising: a) determining the
abundance of the bacteria a biological sample obtained from the
subject; b) comparing the abundance to a reference level from
patients that do not respond to immune checkpoint inhibitor
therapy; or patients that respond to immune checkpoint inhibitor
therapy; wherein if the reference level is from patients that do
not respond to immune checkpoint inhibitor therapy, then an
increase in the abundance of each of the bacteria compared to the
reference level, is indicative that the subject will respond to
therapy with an immune checkpoint inhibitor or wherein if the
reference level is from patients that do respond to immune
checkpoint inhibitor therapy, then the same or substantially the
same or an increase in abundance of each of the bacteria, is
indicative that the subject will respond to therapy with an immune
checkpoint inhibitor. 26. The method according to aspect 24, the
method comprising: a) determining the abundance of the bacteria a
biological sample obtained from the subject and; b) comparing the
abundance to a reference level from cancer patients or healthy
subjects and c) applying random forest analysis. 27. The method
according to any of aspects 24 to 26, the method comprising the
step of predicting a response. 28. The method according to any of
aspects 24 to 27, where if the subject is predicted to be a
non-responder, an anti cancer therapy is administered which is not
an immune checkpoint inhibitor. 29. The method according to any of
aspects 24 to 28, where if the subject is predicted to be a
non-responder, a composition comprising isolated bacteria from one
or more species is administered wherein the bacteria comprise a
sequence selected from SEQ ID 1 to 15 or a sequence having at least
98.7% sequence identity with a nucleic acid sequence selected from
SEQ ID NOs: 1 to 15. 30. A method according to aspect 29, where if
the subject is predicted to be a non-responder, a composition
comprising isolated bacteria selected from at least two species is
administered wherein the bacteria from the first species comprise a
16S rDNA sequence having at least 98.7% sequence identity with a
nucleic acid sequence according to SEQ ID NO: 1, and the bacteria
from the second species comprise a 16S rDNA sequence having at
least 98.7% sequence identity with a nucleic acid sequence
according to SEQ ID NO: 2. 31. A method according to aspect 29 or
31, wherein the composition further comprises isolated bacteria
from at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13 different
species wherein the bacteria comprise a 16S rDNA sequence selected
from a sequence having at least 98.7% sequence identity with a
nucleic acid sequence according to SEQ ID NO: 3 to 15. 32. The
method according to any of aspects 24 to 27, where if the subject
is predicted to be a responder, an immune checkpoint inhibitor
therapy is administered.
Further aspects and embodiments of the invention will be apparent
to those skilled in the art given the present disclosure including
the following experimental exemplification.
Unless otherwise defined herein, scientific and technical terms
used in connection with the present disclosure shall have the
meanings that are commonly understood by those of ordinary skill in
the art. While the foregoing disclosure provides a general
description of the subject matter encompassed within the scope of
the present invention, including methods, as well as the best mode
thereof, of making and using this invention, the following examples
are provided to further enable those skilled in the art to practice
this invention and to provide a complete written description
thereof. However, those skilled in the art will appreciate that the
specifics of these examples should not be read as limiting on the
invention, the scope of which should be apprehended from the claims
and equivalents thereof appended to this disclosure. Various
further aspects and embodiments of the present invention will be
apparent to those skilled in the art in view of the present
disclosure.
All documents mentioned in this specification are incorporated
herein by reference in their entirety, including any references to
gene accession numbers and references to patent publications.
"and/or" where used herein is to be taken as specific disclosure of
each of the two specified features or components with or without
the other. For example, "A and/or B" is to be taken as specific
disclosure of each of (i) A, (ii) B and (iii) A and B, just as if
each is set out individually herein. Unless context dictates
otherwise, the descriptions and definitions of the features set out
above are not limited to any particular aspect or embodiment of the
invention and apply equally to all aspects and embodiments which
are described.
The invention is further described in the non-limiting
examples.
Example 1 Identification of Gut Bacteria and Isolates Driving
Response to Immunotherapy
The inventors have analysed how the microbiome of melanoma patients
impacts response to immune checkpoint inhibitor therapy in the
MELRESIST study. This study was conducted at Cambridge University
Hospitals and was performed with the best standards in sample
collection and processing. The study involved 69 patients many of
which had longitudinal faecal sampling. The inventors analysed the
relative abundance of gut bacteria in the baseline MELRESIST faecal
samples by performing shotgun metagenomic sequencing. The
metagenomic sequencing was analysed using a comprehensive and
highly curated reference genome database primarily built on
reference-quality genomes from cultured isolates. This
reference-based metagenomic analysis gives highly sensitive and
accurate identification of bacteria (Forster et al Nat Biotechnol.
2019; 37: 188). To support this analysis, the inventors re-analysed
three additional shotgun metagenomic datasets from melanoma
patients about to receive immune checkpoint inhibitor therapy using
the same analysis platform.
The microbiome was examined by machine teaming approaches to select
the specific bacterial species most predictive of response to
immune checkpoint inhibitor therapy. For the first time in the
field, a consistent microbiome signature associated with and highly
predictive of response across multiple studies was identified. The
size and quality of the MELRESIST dataset, the comprehensive and
accurate identification of bacteria by reference-based metagenomic
analysis and machine learning analysis all contributed to the
discovery of this cross-study microbiome signature. The signature
also further validates the central importance of the gut microbiome
as a primary driver of immune checkpoint inhibitor response. This
provides the basis for both a predictive biomarker and Live
Bacterial Therapeutic co-therapy to increase the proportion of
patients responding to checkpoint inhibitors. Using feature
reduction steps, this microbiome signature was reduced to small
consortia of bacteria comprising species more abundant in patients
that response to immunotherapy. These smaller consortia are still
predictive of response across studies, so can act as a biomarker.
In addition, these consortia can form a live bacterial therapeutic
for the co-administration with immune checkpoint inhibitors in the
treatment of cancer.
This analysis enabled the identification of strains isolates
representing thirteen species in the consortia. Dendritic cells
stimulated with these strains, individually or as consortia of up
to nine, potently activated Cytotoxic T Lymphocytes. Two consortia
of nine were also tested in a syngeneic mouse model of cancer and
both consortia demonstrated tumour growth inhibition. These results
validate the bacteria as drivers of anti-tumour response.
1.1 Discovery Based on MELRESIST Clinical Study
MELRESIST is a study performed at Cambridge University Hospitals in
which 69 advanced melanoma patients gave a faecal sample prior to
and/or following treatment with anti-PD1 based immunotherapy.
Complete clinical metadata, including response to therapy,
antibiotic use and toxicities, was also recorded. A rigorous sample
collection protocol was used to ensure the highest possible
standards. The DNA was extracted in a single batch at Microbiotica,
and shotgun metagenomics performed. Shotgun metagenomics sequencing
is well known in the art and for example described in Quince, C. et
al, Shotgun metagenomics, from sampling to analysis. Nat Biotechnol
35, 833-844 (2017).
Reference-based metagenomics was used to analysis the sequences of
the baseline stool samples to give more sensitive and specific
identification of bacteria. The accuracy is further improved by a
bioinformatic tool to mask mobile elements thereby reducing
spurious signals caused by horizontal gene transfer. Suitable
methods are also described in WO2020065347 incorporated by
reference. Additional classification filtering removes mis-assigned
reads caused by contamination and gene duplication. The platform
can accurately classify over 95% of the metagenomic reads leading
to a precise mapping of the abundance of almost every bacterium in
the sample.
To support and validate the analysis, three additional datasets
from melanoma patients about to undergo immune checkpoint inhibitor
therapy were reanalysed using the Microbiotica high-precision
platform. These were: Frankel Neoplasia (2017) 19:848, Advanced
melanoma, 39 patients Gopalakrishnan et al and Wargo Science (2018)
359:97, Metastatic melanoma, 25 patients (referenced as Wargo in
figures) Matson et al and Gajewski Science (2018) 359:104,
Metastatic melanoma, 39 patients (referenced as Gajewski in
figures) 1.2 Bioinformatic Analysis to Derive Microbiome-Signatures
Predictive of Response to Immunotherapy
The baseline samples from MELRESIST were used to define a signature
of response by linking the relative abundance of each bacteria in a
sample to the clinical outcome data. In the primary analysis stable
disease, partial response and complete response at 6 months were
all determined to be a response and progressive disease was
considered non-response. Machine learning approaches, including
Random Forest models, were used to select species providing the
most power as part of a signature to predict response.
The random forest classifier is an algorithm based on the results
of many decision trees. In a single decision tree, features are
selected iteratively that best separate samples into responder and
non-responder categories, until all features are utilized. In the
case of prevalence data, these features could be presence or
absence of a given species, where presence of a single species
might be preferentially associated with responder samples, or vice
versa. Alternatively, relative abundance of a given species might
be predictive of response, in which it could be either more or less
abundant in responder samples. Since a single decision tree
typically overfits data and does not produce robust results, random
forests are often used instead. A random forest classifier is based
on many different decision trees, where each tree only uses a
subset of the available data, for example randomly leaving out 20%
of the observed species for each tree. In some cases, a subset of
the samples is used for training the random forest. The random
forest classifier thus learns which signals are strongest across
all possible features and samples. For all random forest models,
out-of-bag error was used to prevent overoptimistic performance and
improve generalizability.
The inventors expanded the analysis by including the additional
melanoma datasets to identify the bacteria linked to response
across multiple studies. First, the data from the different studies
was standardised, for example the response criteria was changed to
be consistent with the MELRESIST study where necessary. A signature
was then generated using the machine learning process on the
combined dataset of all four melanoma datasets. The ability of this
signature to function as a biomarker was then tested on the
combined dataset, and it predicted whether a patient would respond
to therapy with an accuracy of 91% (FIG. 1A). The Receiver
Operating Characteristic (ROC) curve of this analysis gave an area
under the curve (AUC) of 0.98 (FIG. 1C) thereby confirming how
highly predictive this signature is. Importantly, the signature was
83-100% accurate when tested against the studies individually (FIG.
1B), and the ROC curves gave AUCs from 0.96 to 1 (FIG. 1D). This is
the first demonstration of a microbiome based predictive biomarker
that accurately predicts response across studies.
To progress the signature as a biomarker and select bacteria for
inclusion in a Live Bacterial Therapeutic, the inventors identified
the bacteria most robustly associated with response. The species
that were consistently increased in abundance in responding
patients from three or all four studies were selected to be
advanced. Subsequently, a filtering step was applied to choose the
bacteria with the cleanest signal by excluding species where the
metagenomic reads did not broadly and evenly cover the genome.
The entire analysis was repeated from the start but excluding
patients with stable disease, where possible, to focus on bacteria
linked to a better clinical response. This reanalysis overlapped
considerably with the first thereby validating it and was used to
refine the final list of species. These analyses produced a list of
15 bacterial species, consortium 1, all increased in abundance in
melanoma patients that subsequently responded to immune checkpoint
inhibitor therapy across multiple studies (see Table 1 and 3). The
robustness of this reduced signature was demonstrated by repeating
the test as a biomarker in the combined dataset, and it predicted
whether a patient would respond to therapy with an accuracy of 77%
(FIG. 2A). The Receiver Operating Characteristic (ROC) curve of
this analysis gave an area under the curve (AUC) of 0.8 (FIG. 2C)
thereby confirming how highly predictive this signature is.
Importantly, the signature was 67-84% accurate when tested against
the studies individually (FIG. 2B), and the ROC gave AUCs from 0.73
to 0.88 (FIG. 2D). Six additional consortia 2, 3, 4, 5, 6 and 10
composed of 9 or 12 species (Table 3) from the 15 were also tested
as biomarkers, and had good predictivity of response both in the
combined dataset and the individual studies (FIGS. 3-7 and 17).
Thus, the results show that the bacteria identified can be used as
predictive biomarker for response to anti-PD1 therapy in melanoma
patients and also as a bacterial co-therapy to increase the
proportion of melanoma patients responding to checkpoint
inhibitors.
To understand if the bacteria could have utility in other cancer
indications where checkpoint inhibitors are used, the inventors
analysed the predictive value of the full signature in a Non-Small
Cell Lung Cancer (NSCLC) patient cohort (Routy et al 2018 Science
359:91-97). The study sampled patients stool prior to anti-PD1
based therapy, and subjected it to shotgun metagenomic sequencing.
This was reanalysed using the Microbiotica high-precision platform.
The fifteen species in consortium 1 were predictive of whether
NSCLC patients would respond to anti-PD1 therapy (ROC AUC=0.722;
FIG. 8). Therefore, the bacteria described herein and discovered in
melanoma patients are also linked to response in NSCLC. This shows
that the bacteria described herein can be used as predictive
biomarkers in another cancer indication. Moreover, this also
suggests that the bacteria described herein can be used as a
bacterial co-therapy in other cancer indications.
1.3 Selection of Bacterial Isolates
The reference-based metagenomic analysis using genomes from
cultured isolates enables the identified bacteria to be linked back
to isolates of the specific strains and/or closely related strains
in the associated culture collection. All available strains
representing the species in table 1 underwent in silico
characterisation to select for strains with a desirable
developability and safety profile. The primary selection criteria
consisted of anti-microbial resistance, bacteriophage production,
and sporulation. Strains with a good profile were selected for
further testing. These were expanded, cell banks generated, and
growth characterised to enable testing in in vitro assays and in
vivo models. In addition, each strain has undergone full
developability and safety testing by laboratory testing and in
silico analysis. For each genome assembly, 16S rDNA regions were
identified in two ways. Firstly, using barmap
(https://github.com/tseemann/barmap), and secondly by extracting,
in silico, sequences of the desired length (between 1200 and 1800
bp) by searching for DNA matches to the 7F
(5'-AGAGTTTGATYMTGGCTCAG-3) (SEQ ID NO. 30) 1510R
(5'-ACGGYTACCTTGTTACGACTT-3) (SEQ ID NO. 31) universal 16S primers.
Where multiple overlapping 16S sequences were extracted from an
assembly, the longest was retained.
1.4 Host Interaction
The lead bacteria have been selected based on a strong association
with clinical response across multiple studies, and, therefore, are
considered suitable candidates for inclusion in a Live Bacterial
Therapeutic. To understand the mechanism of action, the bacteria
have been profiled individually, as a complete consortium and as
sub-consortia in several in vitro assays with human cells.
Cytotoxic T Lymphocytes (CTLs) are a significant effector cell in
anti-tumour immune responses by directly lysing tumour cells via
granzyme B and perforin release and production of cytokines such as
IFN.gamma.. CTLs can express co-stimulatory and co-inhibitory
receptors. Immune checkpoint inhibitor therapies block the
suppression of CTL activity by blocking the interaction between
co-inhibitory receptor (eg PD-1) and their ligands (eg PD-L1). The
later can be expressed by tumour cells as a mechanism to escape
immune-mediated depletion, which is reversed by checkpoint
inhibitor therapy. CTLs are activated and educated by dendritic
cells, which are a sentinel innate immune cells that have many
receptors to sense and respond to bacteria. Therefore, the bacteria
identified (individually or as consortia) were tested for an
ability to stimulate dendritic cells (DCs), and then if these DCs
activate CTLs.
Bacterial strains representing thirteen of the fifteen species were
identified and grown in bacterial media. These were washed and
added in co-cultured with human monocyte-derived DCs in anaerobic
conditions. Antibiotics were then added and the DCs cultured in an
aerobic environment. The activation of DCs was measured by
upregulation of the maturation markers CD88 (a co-stimulatory
ligand) and CD83. Eleven of the thirteen species robustly induced
expression of both markers with Gordonibacter urolithinfaciens and
Alistipes indictincus being poor activators of DC maturation (FIGS.
9A and 9B). Indeed, many induced a similar level of CD86 and CD83
express as the positive controls, lipopolysaccharide (LPS), Poly
I:C and Salmonella typhimurium, all of which are known to be very
potent activators of DCs. Two consortia of nine species (Consortia
5 and 6), as well as sub-consortia of consortium 6 containing six,
three and two species all also triggered DC maturation as measured
by CD86 and CD83 upregulation (FIG. 9B-9E). The bacteria also
triggered cytokine release from the DCs. IL-12 is a very important
cytokine for the priming of a CTL response, and IL-10 is associated
with suppression of T cell response. Therefore, the ratio of IL-12
to IL-10 was used to measure whether the DCs could be a strong
inducer of a positive CTL response. The nine of the ten species
tested and Consortia 5 and 6 triggered higher levels of IL-12 than
IL-10 even when compared to strong inflammatory stimuli like LPS
and Poly I:C (FIG. 9G). The data from Gordonibacter
urolithinfaciens is not shown because the levels of cytokines
released was too low to make a ratio meaningful. These data
indicate that the bacteria identified as being associated with
response to immune checkpoint inhibitor therapy are by enlarge
potent activators of DC maturation, and release cytokines that
could direct an enhanced T cell response.
To understand how effective these DCs were at stimulating CTLs, the
mature DCs were co-cultured with allogenic CD8 expressing T cells
(CTLs) for 6 days. CTLs activation was quantified by upregulation
of Granzyme B, perforin and IFN.gamma.. Thirteen of the bacterial
species were tested, and all were shown to induce DCs that can
potentially activate CTLs (FIG. 10). The level of activation was
comparable to or better than the strong inflammatory stimuli LPS,
Poly I:C and Salmonella typhimurium. Interesting, even
Gordonibacter urolithinfaciens and Alistipes indictincus were shown
to lead to robust CTLs activation despite being poor stimulators of
CD86 and CD83 expression by DCs. The consortia tested (5, 6, 7, 8
and 9) also all induced strong CTL activation (FIGS. 11 and 12).
These data demonstrate that the bacteria identified as being
associated with response to immune checkpoint inhibitor therapy are
potent activators of a CTL response via stimulation of DCs. This is
true of the individual species and of consortia of two to nine
species. This induction of CTL activation could be a key mechanism
by which the raised abundance of these bacteria leads to enhanced
anti-tumour immunity in the presence of anti-PD1. It could also
indicate that a therapeutic composition comprising these bacteria
could enhance a vaccine response and/or anti-viral immunity.
The bacteria lead to potent CTL activation, so their ability to
kill tumour cells was tested next. In this assay, the CTLs
activated by bacteria-stimulated DCs were co-cultured with the
tumour cell line SKOV-3 cells. All ten of the species tested led to
potent cytolysis of the tumour cells by CTLs as measured by a
decrease in electric impedance. The level of tumour cell killing
compared favourably to the other known strong innate stimuli. The
consortia tested (5, 6, 7, 8 and 9) also led to high levels of
tumour cell killing (FIGS. 13 and 14). These data demonstrate that
the bacteria identified as being associated with response to immune
checkpoint inhibitor therapy are potent activators of an
immune-mediated tumour cell killing. This is true of the individual
species tested and of consortia of two to nine species.
In total, the above data show that the bacterial species identified
as being associated anti-PD-1 response are able to stimulate DCs to
trigger CTLs activation and tumour cell killing. This mechanism is
likely to explain, at least in part, why these bacteria are
associated with response to anti-PD-1 based therapy in melanoma.
This mechanism is associated with immune checkpoint inhibitor
efficacy in multiple tumours indicating that the bacteria described
herein can be used as a bacterial co-therapy in other cancer
indications. Indeed, the bacteria described herein are likely to be
an effective co-therapy with any immunotherapy that enhances CTL
response for example adoptive T cell transfer therapy and CAR-T
cell therapy. Interestingly, two of the strains tested
(Gordonibacter urolithinfaciens and Alistipes indictincus) did not
induce classical markers of DC activation (CD86 and CD83), but the
DCs still induced CTL activation.
The type 1 interferons (IFNs), IFN.alpha. and IFN.beta., are potent
inducers of CTL immunity and can have direct anti-tumour effects.
Plasmacytoid dendritic cells are capable of producing very high
levels of IFN.alpha. and IFN.beta.. To test if the isolated
bacteria associated with anti-PD-1 response induced IFN.alpha.
release, plasmacytoid dendritic cells were stimulated with strains
representing nine of the species. Plasmacytoid dendritic cells did
not tolerate anaerobic conditions, so heat-killed bacteria were
used in an aerobic environment. Seven of the nine strain induced
IFN.alpha. release from plasmacytoid DCs (FIG. 15). This could be
another potential mechanism by which these bacteria enhance
anti-tumour immune responses. Interesting a tonic type 1 interferon
signal from the microbiome has been implicated in enhancing
anti-viral responses in the lung (Bradley et al 2019 Cell Reports
28:245-256). Therefore, the species identified may also potential
drive an anti-viral response and/or anti-viral vaccine
efficacy.
In addition, to the above mechanistic assays two selected consortia
were tested for efficacy in a syngeneic model of cancer. SPF mice
were treated with antibiotics before engrafting the microbiome of a
melanoma patient one day prior to implanting MCA205 tumour cells.
Dosing consortium 5 or 6 by oral gavage induce tumour growth
inhibition (FIG. 16) although not to the same degree as the
positive control (anti-PD1). This shows the anti-tumour potential
of these consortia, and validates the selection of these species by
association with improved clinical outcome. MCA-205 is a
fibrosarcoma cell lines, which further demonstrates that the
bacteria described herein have potential in cancer indications
beyond melanoma. Together the data presented here shows we have
identified bacterial species predictive of response to checkpoint
inhibitor therapy in multiple melanoma studies and in NSCLC. These
species are able to stimulate DCs leading to the activation of CTLs
and tumour cell killing. Two consortia of these species are further
validated in an in vivo cancer model.
TABLE-US-00002 TABLE 2 Sequences SEQ ID 16S rDNA Sequence SEQ ID
AGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAAGT No. 1
CGAACGGAGTTATGCAGAGGAAGTTTTCGGATGGAATCGGCGTAACTTAGTGGCGGA
CGGGTGAGTAACGCGTGGGAAACCTGCCCTGTACCGGGGGATAACACTTAGAAATAG
GTGCTAATACCGCATAAGCGCACAGCTTCACATGAGGCAGTGTGAAAAACTCCGGTGG
TACAGGATGGTCCCGCGTCTGATTAGCCAGTTGGCAGGGTAACGGCCTACCAAAGCG
ACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCC
CAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATG
CAGCGACGCCGCGTGAGTGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGGGAA
GAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGT
AATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGG
CATGACAAGCCAGATGTGAAAACCCAGGGCTCAACCCTGGGACTGCATTTGGAACTG
CCAGGCTGGAGTGCAGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTA
GATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACTGTAACTGACGTTGA
GGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCGGTAAA
CGATGATTGCTAGGTGTAGGTGGGTATGGACCCATCGGTGCCGCAGCTAACGCAATA
AGCAATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGA
CCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAA
GTCTTGACATCCCAATGACGTGTCCGTAACGGGGCATTCTCTTCGGAGCATTGGAGAC
AGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAA
CGAGCGCAACCCTTATCCTTAGTAGCCAGCAGGTAGAGCTGGGCACTCTAGGGAGAC
TGCCGGGGATAACCCGGAGGAAGGCGGGGATGACGTCAAATCATCATGCCCCTTATG
ATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGTGATGTT
GAGCAAATCCCAGAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATG
AAGCTGGAATCGCTAGTAATCGCGAATCAGCATGTCGCGGTGAATACGTTCCCGGGTC
TTGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGCCTGTGACCTAA
CCGCAAGGGAGGAGCAGTCGAAGGCAGGTCTAATAACTGGGGTGAAGTCGTAACAAG
GTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TTTAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 2
GTCGAACGGAGTTATTTTGGAAATCTCTTCGGGGATGGAATTCATAACTTAGTGGCGG
ACGGGTGAGTAACGCGTGAGCAATCTGCCCTTAGGTGGGGGATAACAGCCGGAAACG
GCTGCTAATACCGCATAACACATTGAAGCCGCATGGTTTTGATGTCAAAGATTTATTGC
CTTTGGATGAGCTCGCGTCTGATTAGCTGGTTGGCGGGGTAACGGCCCACCAAGGCG
ACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCC
AGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGC
AGCAACGCCGCGTGATTGAAGAAGGCCTTCGGGTTGTAAAGATCTTTAATTGGGGACG
AATTTTGACGGTACCCAAAGAATAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGGTA
ATACGTAGGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGCGAGTAGGCGGG
CTGGCAAGTTGGGAGTGAAATCCCGGGGCTTAACCCCGGAACTGCTTTCAAAACTGCT
GGTOTTGAGTGATGGAGAGGCAGGCGGAATTCCGTGTGTAGCGGTGAAATGCGTAGA
TATACGGAGGAACACCAGTGGCGAAGGCGGCCTGCTGGACATTAACTGACGCTGAGG
AGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACG
ATGGATACTAGGTGTGGGAGGTATTGACCCCTTCCGTGCCGGAGTTAACACAATAAGT
ATCCCACCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCC
GCACAAGCAGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTC
TTGACATCCCTCTGACCGCCCTAGAGATAGGGTTTCCCTTCGGGGCAGAGGTGACAG
GTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACG
AGCGCAACCCTTACGGTTAGTTGATACGAAAGATCACTCTAGCCGGACTGCCGTTGAC
AAAACGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGACCTGGGCTA
CACACGTACTACAATGGCAGTCATACAGAGGGAAGCAAAACAGTGATGTGGAGCAAAT
CCCTAAAAGCTGTCCCAGTTCAGATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGAA
TTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACACA
CCGCCCGTCACACCATGAGAGCCGGTAATACCCGAAGTCCGTAGCCTAACCGCAAGG
AGGGCGCGGCCGAAGGTAGGACTGGTAATTAGGGTGAAGTCGTAACAAGGTAGCCGT
ATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TTTAAGAGTTTGATCCTGGCTCAGGACGAACGCTGGCGGCGTGCCTAACACATGCAAG No. 3
TCGAACGAAGCTTGATTTCTGATTTTTTCGGAATGACGAATGATATGACTGAGTGGCGG
ACGGGTGAGTAACGCGTGAGCAACCTGCCCTTOGGAACGGGATAGTGTCTGGAAACG
GACAGTAATACCGTATAATATATATTGATCGCATGGTTGATATATCAAAACTGAGGTGC
CGAAGGATGGGCTCGCGTCTGATTAGATAGTTGGTGGGGTAACGGCCTACCAAGTCG
ACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCC
AGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGC
AGCAACGCCGCGTGAAGGAAGACGGTTTTCGGATTGTAAACTTCTGTTCTTAGTGAAG
AATAATGACGGTAGCTAAGGAGCAAGCCACGGCTAACTACGTGCCAGCAGCCGCGGT
AATACGTAGGTGGCAAGCGTTGTCCGGAATTACTGGGTGTAAAGGGAGCGTAGGCGG
GATGCCAAGTCAGCTGTGAAAACTATGGGCTTAACTTGTAGACTGCAGTTGAAACTGG
TATTCTTGAGTGAAGTAGAGGTTGGCGGAATTCCGAGTGTAGOGGTGAAATGCGTAGA
TATTCGGAGGAACACCGGTGGCGAAGGCGGCCAACTGGGCTTTAACTGACGCTGAGG
CTCGAAAGTGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACACTGTAAACGA
TGATAACTAGGTGTGGGGGGTCTGACCCCTTCCGTGCCGCAGCTAACGCAATAAGTTA
TCCACCTGGGGAGTACGACCGCAAGGTTGAAACTCAAAGGAATTGACGGGGACCCGC
ACAAGCAGTGGATTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGCACTT
GACATCCGACTAACGAAGTAGAGATACATTAGGTGCCCTTCGGGGAAAGTCGAGACA
GGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTOCCGCAAC
GAGCGCAACCCCTGCCATTAGTTGCTACGCAAGAGCACTCTAATGGGACCGCTACCG
ACAAGGTGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGTGCTGGGC
TACACACGTAATACAATGGCCATCAACAAAGAGAAGCAATACCGCGAGGTGGAGCAAA
ACTATAAAAATGGTCTCAGTTCGGACTGCAGGCTGCAACCCGCCTGCACGAAGTTGGA
ATTGCTAGTAATCGTGGATCAGCATGCCACGGTGAATACGTTCCCGGGTCTTGTACAC
ACCGCCCGTCACACCATGGGAGTTGGTAACACCCGAAGTCAGTAGTCTAACCGCAAG
GAGGACGCTGCCGAAGGTGGGATTGACGACTGGGGTGAAGTCGTAACAAGGTAGCC
GTATCAGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
ATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGGCAGGCTTAACACATGCAA No. 4
GTCGAGGGGCAGCATAATGGTAGCAATACTATTGATGGCGACCGGCGGACGGGTGCG
TAACGCGTATGCAACCTACCCTTTACAGGGGGATAACACTGAGAAATCGGTACTAATA
CCCCATAATATTCTGGGAGGCATCTTTOGGAGTTGAAAGCTTTGGTGGTAAAGGATGG
GCATGCGTTGTATTAGCTAGTTGGTAAGGTAACGGCTTACCAAGGCGACGATACATAG
GGGGACTGAGAGGTTAACCCCCCACATTGGTACTGAGACACGGACCAAACTCCTACG
GGAGGCAGCAGTGAGGAATATTGGTCAATGGACGGAAGTCTGAACCAGCCATGCCGC
GTGCAGGAAGACGGCTCTATGAGTTGTAAACTGOTTTTGTACGAGGGTAAACGCAGAT
ACGTGTATCTGCCTGAAAGTATCGTACGAATAAGGATCGGCTAACTCCGTGCCAGCAG
CCGCGGTAATACGGAGGATCCAAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGT
AGGCGGTTTAGTAAGTCAGCGGTGAAATTTTGGTGOTTAACACCAAACGTGCCGTTGA
TACTGCTGGGCTAGAGAGTAGTTGCGGTAGGCGGAATGTATGGTGTAGCGGTGAAAT
GCTTAGAGATCATACAGAACACCGATTGCGAAGGCAGCTTACCAAACTATATCTGACG
TTGAGGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCAG
TAAACGATGATAGCTCGTTGTCGGCGATACACAGTCGGTGACTAAGAGAAATCGATAA
GCTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGGC
CCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCG
GGCTTGAAAGTTACTGACGATTCTGGAAACAGGATTTCCCTTCGGGGCAGGAAACTAG
GTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAACG
AGCGCAACCCCTACTGATAGTTGCCATCAGAGCGTTTGAGCGATCAAACAAGCTGGGC
ACTCTATCGGGACTGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAG
CACGGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGTAGGTACAGAGGGCAGC
CACCCAGTGATGGGGAGCGAATCTCGAAAGCCTATCTCAGTTCGGATTGGAGGCTGA
AACTCGCCTCCATGAAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGA
ATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGGAGTTGGGGGTGCCT
GAAGTTCGTGACCGAAAGGAGCGACCTAGGGCAAAACCGATGACTGGGGCTAAGTCG
TAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ ID
ATGGAGAGTTTGATCCTGGCTCAGGATAAACGCTAGCGGCAGGCCTAACACATGCAA No. 5
GTCGAGGGGCAGCGGGTGGAGTATTTCGGTACTCCTGCCGGCGACCGGCGCACGGG
TGCGTAACGCGTATGCAACCTACCTTTAACAGGGGGATAATCCGAAGAAATTTGGTCT
AATACCCCATAATATCATTTAAGGCATCTTAGATGGTTGAAAATTCCGATGGTTAGAGA
TGGGCATGCGTTGTATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCTACGATACA
TAGGGGGACTGAGAGGTTTTCCCCCCACACTGGTACTGAGACACGGACCAGACTCCT
ACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGACGCAAGTCTGAACCAGCCATGC
CGCGTGCAGGATGAAGGTGCTATGCATTGTAAACTGCTTTTGTACGAGGGTAAATGCA
GGTACGTGTACCTGTTTGAAAGTATCGTACGAATAAGGGTCGGCTAACTCCGTGCCAG
CAGCCGCGGTAATACGGAGGACCCGAGCGTTATCCGGATTTATTGGGTTTAAAGGGT
GCGTAGGCGGATTAGTAAGTTAGAGGTGAAAGCTCGATGCTCAACATCGAAATTGCCT
CTGATACTGTTAGTCTAGAGTATAGTTGCGGAAGGCGGAATGTGTGGTGTAGCGGTGA
AATGCTTAGATATCACACAGAACACCGATTGCGAAGGCAGCTTTCCAAGCTATTACTGA
CGCTGATGCACGAAAGCGTGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCACGC
CGTAAACGATGATAACTCGTTGCAGGCGATACACAGTCTGTGACTTAGCGAAAGCGTT
AAGTTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGG
CCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCC
GGGCTTGAAAGTTAGCGACGGATCCTGAAAGGGGTCTTCTCTTCGGAGCGCGAAACT
AGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAA
CGAGCGCAACCCCTACTGTTAGTTACCAGCACGTCAAGGTGGGCACTCTAGCAGGAC
TGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACG
TCCGGGGCGACACACGTGTTACAATGGTCGGTACAGAGGGTCGCTACCCCGTGAGGG
GATGCCAATCTCGAAAGCCGATCTCAGTTCGGATTGGAGGCTGAAACTCGCCTCCATG
AAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGGG
CCTTGTACACACCGCCCGTCAAGCCATGGGAGTTGGGGGTGCCTGAAGTACGTGACC
GCAAGGAGCGTCCTAGGGCAAAACCGATGACTGGGGCTAAGTCGTAACAAGGTAGCC
GTACCGGAAGGTGCGGCTGGAACACCTCCTT SEQ ID
ACGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 6
GTCGAACGGTTAAGGCGCCTTCGGGCGCGAATAGAGTGGCGAACGGGTGAGTAACAC
GTGACCAACCTGCCCCCCTCCCCGGGATAACGCGAGGAAACCCGCGCTAATACCGGA
TACTCCGCCCCTCCCGCATGGGAGGGGCGGGAAAGCCCCGACGGAGGGGGATGGG
GTCGCGGCCCATTAGGTAGACGGCGGGGCAACGGCCCACCGTGCCTGCGATGGGTA
GCCGGGTTGAGAGACCGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTAC
GGGAGGCAGCAGTGGGGAATTTTGCGCAATGGGGGGAACCCTGACGCAGCAACGCC
GCGTGCGGGACGAAGGCCTTCGGGTTGTAAACCGCTTTCAGCAGGGAAGAAGTTGAC
GGTACCTGCAGAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAG
GGGGCGAGCGTTATCCGGATTCATTGGGCGTAAAGCGCGCGTAGGCGGCCCGTCAA
GCGGAACCTCTAACCCGAGGGCTCAACCCCCGGCCGGGTTCCGAACTGGCAGGCTC
GAGTTTGGTAGAGGAAGATGGAATTCCCGGTGTAGCGGTGGAATGCGCAGATATCGG
GAAGAACACCGATGGCGAAGGCAGTCTTCTGGGCCATCAACTGACGCTGAGGCGCGA
AAGCTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCCAGCCGTAAACGATGGG
TGCTAGGTGTGGGGGGATCATCCCTCCGTGCCGCAGCCAACGCATTAAGCACCCCGC
CTGGGGAGTACGGCCGCAAGGCTAAAACTCAAAGGAATTGACGGGGGCCCGCACAA
GCAGCGGAGCATGTGGCTTAATTCGAAGCAACGCGAAGAACCTTACCAGGGCTTGAC
ATGCTGGTGAAGCCGGGGAAACCCGGTGGCCGAGAGGAGCCAGCGCAGGTGGTGCA
TGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAAC
CCCTGCCATATGTTGCCAGCATTCAGTTGGGGACTCATATGGGACTGCCGGCGTCAA
GCCGGAGGAAGGTGGGGACGACGTCAAGTCATCATGCCCTTTATGCCCTGGGCTGCA
CACGTGCTACAATGGCCGGTACAACGGGCCGCGACCTGGCGACAGGAAGCGAATCC
CTCAAAGCCGGCCCCAGTTCGGATCGGAGGCTGCAACCCGCCTCCGTGAAGTCGGA
GTTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACA
CACCGCCCGTCACACCACCCGAGTCGTCTGCACCCGAAGCCGCCGGCCGAACCCGC
AAGGGGCGGAGGCGTCGAAGGTGTGGAGGGTAAGGGGGGTGAAGTCGTAACAAGGT
AGCCGTACCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
ATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCATGCCTAATACATGCAAG No. 7
TCGAACGAAGTOTTTAGGAAGCTTGCTTCCAAAGAGACTTAGTGGCGAACGGGTGAGT
AACACGTAGGTAACCTGCCCATGTGCCCGGGATAACTGCTGGAAACGGTAGCTAAAAC
CGGATAGGTATGAGGGAGGCATCTTCCTCATATTAAAGCACCTTCGGGTGTGAACATG
GATGGACCTGCGGCGCATTAGCTGGTTGGTGAGGTAACGGCCCACCAAGGCGATGAT
GCGTAGCCGACCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAAACT
CCTACGGGAGGCAGCAGTAGGGAATTTTCGTCAATGGGGGGAACCCTGAACGAGCAA
TGCCGCGTGTGTGAAGAAGGTCTTCGGATCGTAAAGCACTGTTGTAAGTGAAGAATGC
CATATAGAGGAAATGCTATGTGGGTGACGGTAGCTTACCAGAAAGCCACGGCTAACTA
CGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATCATTGGGCG
TAAAGGGTGCGTAGGTGGCACGATAAGTCTGAAGTAAAAGGCAACAGCTCAACTGTTG
TATGCTTTGGAAACTGTCGAGCTAGAGTGCAGAAGAGGGCGATGGAATTCCATGTGTA
GCGGTAAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGTCGCCTGGTC
TGTAACTGACACTGATGCACGAAAGCGTGGGGAGCAAATAGGATTAGATACCCTAGTA
GTCCACGCCGTAAACGATGAGAACTAAGTGTTGGAGAGATTCAGTGCTGCAGTTAACG
CAATAAGTTCTCCGCCTGGGGAGTATGCACGCAAGTGTGAAACTCAAAGGAATTGACG
GGGGCCCGCACAAGCGGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTT
ACCAGGCCTTGACATGGATATAAATGTTCTAGAGATAGAAAGATAGCTATATATCACAC
AGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAA
CGAGCGCAACCCTTGTCTTCTGTTACCAGCATTAAGTTGGGGACTCAGGAGAGACTGC
CGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGGCC
TGGGCTACACACGTACTACAATGGCGCCTACAAAGAGCAGCGACACCGCGAGGTGGA
GCGAATCTCATAAAGGGCGTCTCAGTTCGGATTGAAGTCTGCAACTCGACTTCATGAA
GTCGGAATCGCTAGTAATCGCAGATCAGCATGCTGCGGTGAATACGTTCTCGGGCCTT
GTACACACCGCCCGTCAAACCATGGGAGTTGGTAATACCCGAAGCCGGTGGCATAAC
CGCAAGGAGTGAGCCGTCGAAGGTAGGACCGATGACTGGGGTTAAGTCGTAACAAGG
TATCCCTACGGGAACGTGGGGATGGATCACCTCCTTT SEQ ID
TCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 8
GTCGAGCGAAGCACTTAAGTGGATCTCTTCGGATTGAAACTTATTTGACTGAGCGGCG
GACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTAGAAAT
GGCTGCTAATACCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTCCGG
TGGTATGAGATGGACCCGCGTCTGATTAGCTAGTTGGAGGGGTAACGGCCCACCAAG
GCGACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACG
GCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTG
ATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGG
GAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGC
GGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGA
CGGAAGAGCAAGTCTGATGTGAAAGGCTGGGGCTTAACCCCAGGACTGCATTGGAAA
CTGTTTTTCTAGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCG
TAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGTT
GAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTA
AACGATGAATACTAGGTGTCGGGTGGCAAAGCCATTCGGTGCCGCAGCAAACGCAAT
AAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGA
CCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAA
GTCTTGACATCCCTCTGACCGGCCCGTAACGGGGCCTTCCCTTCGGGGCAGAGGAGA
CAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCA
ACGAGCGCAACCCCTATCCTTAGTAGCCAGCAGGTAGAGCTGGGCACTCTAGGGAGA
CTGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTAT
GATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGCGATG
TTGAGCAAATCCCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCA
CGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGG
GTCTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGAC
CCAACCTTACAGGAGGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTA
ACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
CGAAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGACAGGCCTAACACATGCAAGT No. 9
CGAGGGGCAGCGGAGAGGTAGCAATACCTTTGCCGGCGACCGGCGCACGGGTGAGT
AACACGTATGCAATCCACCTGTAACAGGGGGATAACCCGGAGAAATCCGGACTAATAC
CCCATAATATGGGCGCTCCGCATGGAGAGTCCATTAAAGAGAGCAATTTTGGTTACAG
ACGAGCATGCGCTCCATTAGCCAGTTGGCGGGGTAACGGCCCACCAAAGCGACGATG
GATAGGGGTTCTGAGAGGAAGGTCCCCCACATTGGAACTGAGACACGGTCCAAACTC
CTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGTCGGCAGACTGAACCAGCCAA
GTCGCGTGAGGGAAGACGGCCCTACGGGTTGTAAACCTCTTTTGTCGGAGAGTAAAG
TACGCTACGTGTAGTGTATTGCAAGTATCCGAAGAAAAAGCATCGGCTAACTCCGTGC
CAGCAGCCGCGGTAATACGGAGGATGCGAGCGTTATCCGGATTTATTGGGTTTAAAG
GGTGCGTAGGCGGCACGCCAAGTCAGCGGTGAAATTTCCGGGCTCAACCCGGACTGT
GCCGTTGAAACTGGCGAGCTAGAGTGCACAAGAGGCAGGCGGAATGCGTGGTGTAG
CGGTGAAATGCATAGATATCACGCAGAACCCCGATTGCGAAGGCAGCCTGCTAGGGT
GCGACAGACGCTGAGGCACGAAAGCGTGGGTATCGAACAGGATTAGATACCCTGGTA
GTCCACGCAGTAAACGATGAATACTAACTGTTTGCGATACAATGTAAGCGGTACAGCG
AAAGCGTTAAGTATTCCACCTGGGGAGTACGCCGGCAACGGTGAAACTCAAAGGAATT
GACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAA
CCTTACCCGGGCTCAAACGCAGGGGGAATGCCGGTGAAAGTCGGCAGCTAGCAATAG
TCACCTGCGAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGCTTAA
GTGCCATAACGAGCGCAACCCCTATGGACAGTTACTAACGGGTGAAGCCGAGGACTC
TGTCTAGACTGCCGGCGCAAGCCGCGAGGAAGGTGGGGATGACGTCAAATCAGCAC
GGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGCAGGTACAGAAGGCAGCCAG
TCAGCAATGACGCGCGAATCCCGAAAACCTGTCTCAGTTCGGATTGGAGTCTGCAACC
CGACTCCATGAAGCTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATA
CGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGAAGCCGGGAGTACCTGAA
GCATGCAACCGCAAGGAGCGTACGAAGGTAATACCGGTAACTGGGGCTAAGTCGTAA
CAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ ID
ATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGGCAGGCCTAACACATGCAA No. 10
GTCGAGGGGCAGCGGGATTGAAGCTTGCTTCAATCGCCGGCGACCGGCGCACGGGT
GCGTAACGCGTATGCAACCTACCCAGAACAGGGGGATAACACTGAGAAATTGGTACTA
ATATCCCATAACATCATAAGGGGCATCCCTTTTGGTTGAAAACTCCGGTGGTTCTGGAT
GGGCATGCGTTGTATTAGCTAGTTGGTGAGGTAACGGCTCACCAAGGCAACGATACAT
AGGGGGACTGAGAGGTTAACCCCCCACATTGGTACTGAGACACGGACCAAACTCCTA
CGGGAGGCAGCAGTGAGGAATATTGGTCAATGGACGCAAGTCTGAACCAGCCATGCC
GCGTGCAGGAAGACGGCTCTATGAGTTGTAAACTGCTTTTGTACTAGGGTAAACTCAG
ATACGTGTATCTGACTGAAAGTATAGTACGAATAAGGATCGGCTAACTCCGTGCCAGC
AGCCGCGGTAATACGGAGGATTCAAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGC
GTAGGCGGTTTGATAAGTTAGAGGTGAAATACCGGTGCTTAACACCGGAACTGCCTCT
AATACTGTTGAGCTAGAGAGTAGTTGCGGTAGGCGGAATGTATGGTGTAGCGGTGAAA
TGCTTAGAGATCATACAGAACACCGATTGCGAAGGCAGCTTACCAAACTATATCTGAC
GTTGAGGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCA
GTAAACGATGATAACTCGCTGTCGGCGATACACAGTCGGTGGCTAAGCGAAAGCGATA
AGTTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGG
CCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCC
GGGCTTGAAAGTTAGTGACGGATCTGGAAACAGGTOTTCCCTTCGGGGCGCGAAACT
AGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAA
CGAGCGCAACCCCTACCGTTAGTTGCCATCAGGTCAAGCTGGGCACTCTGACGGGAC
TGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAGCACGGCCCTTACG
TCCGGGGCCACACACGTGTTACAATGGTAGGTACAGAGGGCAGCTACCCAGCGATGG
GATGCGAATCTCGAAAGCCTATCTCAGTTCGGATCGGAGGCTGAAACCCGCCTCCGT
GAAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATACGTTCCCGG
GCCTTGTACACACCGCCCGTCAAGCCATGGAAGCTGGGGGTGCCTGAAGTTCGTGAC
CGCAAGGAGCGACCTAGGGCAAAACCGGTGACTGGGGCTAAGTCGTAACAAGGTAGC
CGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ ID
TCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 11
GTCGAGCGAAGCACTTGCCATTGACTCTTCGGAAGATTTGGCATTTGACTGAGCGGCG
GACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGAATAACAGTTAGAAAT
GGCTGCTAATGCCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTGAGG
TGGTATGAGATGGGCCCGCGTCTGATTAGGTAGTTGGCGGGGTAACGGCCCACCAAG
CCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACG
GCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTG
ATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGG
GAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGC
GGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGA
CGGACGGGCAAGICTGATGTGAAAGCCCGGGGCTTAACCCCGGGACTGCATTGGAAA
CTGTCCATCTTGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGT
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGTTGCAAAGCAATCCGGTGCCGCAGCAAACGCAG
TAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGG
ACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCA
AGTCTTGACATCTGCCTGACCGTTCCTTAACCGGAACTTTCCTTCGGGACAGGCAAGA
CAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCA
ACGAGCGCAACCCCTGTCCTTAGTAGCCAGCAGTCCGGCTGGGCACTCTAGGGAGAC
TGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATG
ATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGTGGTGACAC
TGAGCAAATCTCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCAC
GAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGT
CTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCT
AACCGCAAGGGAGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAAC
AAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TTATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 12
GTCGAACGAAGCATTTAAGACGGATTCTTTCGGGATGAAGACTTTTATGACTGAGTGG
CGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCACACAGGGGGATAGCAGTTGGAA
ACGGCTGATAATACCGCATAAGCGCACAGTACCGCATGGTACAGTGTGAAAAACTCCG
GTGGTGTGAGATGGACCCGCGTCTGATTAGCTTGTTGGCAGGGTAACGGCCTACCAA
GGCAACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACAC
GGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCT
GATGCAGCGACGCCGCGTGAGTGAAGAAGTAATTCGTTATGTAAAGCTCTATCAGCAG
GGAAGATAGTGACGGTACCTGACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCG
CGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGG
TGGCATCACAAGTCAGAAGTGAAAGCCCGGGGCTCAACCCCGGGACTGCTTTTGAAA
CTGTGGAGCTGGAGTGCAGGAGAGGCAAGTGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTGCTGGACTGTAACTGACAC
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGGCTCATAAGAGCTTCGGTGCCGCAGCAAACGCA
ATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGG
GACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTAC
CAAGTCTTGACATCCTCTTGACCGGTCAGTAATGTGACCTTTTCTTCGGAACAAGAGTG
ACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGC
AACGAGCGCAACCCCTATTCTTAGTAGCCAGCATTTAAGGTGGGCACTCTAGGAAGAC
TGCCAGGGATAACCTGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATG
ACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGTGAAGCGAGAGTGTGAGCTT
AAGCAAATCACAAAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGA
AGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCT
TGTACACACCGCCCGTCACACCATGGGAGTCGGAAATGCCCGAAGTCGGTGACCTAA
CGAAAGAAGGAGCCGCCGAAGGCAGGTCTGATAACTGGGGTGAAGTCGTAACAAGGT
AGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TAAAGAGTTTGATCCTGGCTCAGGACGAACGCTGGCGGCACGCTTAACACATGCAAGT No. 13
CGAACGGAGAATATCGAAGCTTGCTTTGATATTCTTAGTGGCGGACGGGTGAGTAACA
CGTGAGTAACCTGCCTCTGAGAGTGGGATAGCTTCTGGAAACGGATGGTAATACCGCA
TGAAATCATAGTATCGCATGGTACAATGATCAAAGATTTATCGCTCAGAGATGGACTCG
CGTCTGATTAGCTAGTTGGTAAGGTAACGGCTTACCAAGGCGACGATCAGTAGCCGGA
CTGAGAGGTTGATCGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGAGG
CAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGATGCCGCGTGGA
GGAAGAAGGTTTTCGGATTGTAAACTCCTGTTGAAGAGGACGATAATGACGGTACTCT
TTTAGAAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGAGCGAG
CGTTGTCCGGAATTACTGGGTGTAAAGGGAGCGTAGGCGGGACGGCAAGTCAGATGT
GAAAACTATGGGCTCAACCCATAGACTGCATTTGAAACTGTTGTTCTTGAGTGAGGTAG
AGGTAAGCGGAATTCCTGGTGTAGCGGTGAAATGCGTAGAGATCAGGAGGAACATCG
GTGGCGAAGGCGGCTTACTGGGCCTTTACTGACGCTGAGGCTCGAAAGCGTGGGGA
GCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAACGATGATTACTAGGTGTGG
GGGGACTGACCCCTTCCGTGCCGCAGTTAACACAATAAGTAATCCACCTGGGGAGTA
CGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGTGGAGTA
TGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGGTOTTGACATCGAGTGACGT
ACCTAGAGATAGGTATTTTCTTCGGAACACAAAGACAGGTGGTGCATGGTTGTCGTCA
GCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTACCATTAGT
TGCTACGCAAGAGCACTCTAATGGGACTGCCGTTGACAAAACGGAGGAAGGTGGGGA
TGACGTCAAATCATCATGCCCCTTATGACCTGGGCTACACACGTACTACAATGGCAATA
TAACAGAGGGAAGCAATACAGCGATGTGGAGCAAATCCCCAAAAATTGTCCCAGTTCA
GATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGAATTGCTAGTAATCGCAGATCAGC
ATGCTGCGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGGGAG
TCGGTAACACCCAAAGCCGGTCGTCTAACCTTCGGGAGGACGCCGTCTAAGGTGGGA
TTGATGACTGGGGTGAAGTCGTAACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATC ACCTCCTTT
SEQ ID ATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAAGT
No. 14 CGAACGAAGCACTCTATTTGATTTTCTTCGGAAATGAAGATTTTGTGACTGAGTGGCGG
ACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTGGAAACG
ACTGCTAATACCGCATAAGCGCACAGGATCGCATGGTCCGGTGTGAAAAACTCCGGT
GGTATGAGATGGACCCGCGTCTGATTAGCCAGTTGGCAGGGTAACGGCCTACCAAAG
CGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGG
CCCAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGA
TGCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGG
GAAGAAGAATGACGGTACCTGACTAAGAAGCACCGGCTAAATACGTGCCAGCAGCCG
CGGTAATACGTATGGTGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGCAG
GCGGTGCGGCAAGTCTGATGTGAAAGCCCGGGGCTCAACCCCGGTACTGCATTGGAA
ACTGTCGTACTAGAGTGTCGGAGGGGTAAGTGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGATAACTGACGC
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGGAGCATTGCTCTTCGGTGCCGCAGCAAACGCAAT
AAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGA
CCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAA
GTCTTGACATCCCGATGACAGAGTATGTAATGTACTTTCTCTTCGGAGCATCGGTGACA
GGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAAC
GAGCGCAACCCCTGTTCTTAGTAGCCAGCGGTTCGGCCGGGCACTCTAGGGAGACTG
CCAGGGATAACCTGGAGGAAGGCGGGGATGACGTCAAATCATCATGCCCCTTATGAC
TTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGCCGTGAGGCCG
AGCAAATCTCAAAAATAACGTCTCAGTTCGGACTGTAGTCTGCAACCCGACTACACGA
AGCTGGAATCGCTAGTAATCGCAGATCAGAATGCTGCGGTGAATACGTTCCCGGGTCT
TGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGTCAGTGACCCAA
CCGCAAGGAGGGAGCTGCCGAAGGCAGGTTCGATAACTGGGGTGAAGTCGTAACAAG
GTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
AGAGTTTGATCCTGGCTCAGGACGAACGCTGGCGGCGCGCCTAACACATGCAAGTCG No. 15
AACGAGAGAGAGGGAGCTTGCTTCCTTGATCGAGTGGCGAACGGGTGAGTAACGCGT
GAGGAACCTGCCTCAAAGAGGGGGACAACAGTTGGAAACGACTGCTAATACCGCATA
AGCCCACGACCCGGCATCGGGAAGAGGGAAAAGGAGCAATCCGCTTTGAGATGGCCT
CGCGTCCGATTAGCTAGTTGGTGAGGTAACGGCCCACCAAGCGACGATCGGTAGCCG
GACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCCAGACTCCTACGGGA
GGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATGCAGCGACGCCGCGT
GGAGGAAGAAGGTCTTCGGATTGTAAACTCCTGTTGTTGAGGAAGATAATGACGGTAC
TCAACAAGGAAGTGACGGCTAACTACGTGCCAGCAGCCGCGGTAAAACGTAGGTCAC
AAGCGTTGTCCGGAATTACTGGGTGTAAAGGGAGCGCAGGCGGGCGATCAAGTTGGA
AGTGAAATCCATGGGCTCAACCCATGAACTGCTTTCAAAACTGGTCGTCTTGAGTAGT
GCAGAGGTAGGCGGAATTCCCGGTGTAGCGGTGGAATGCGTAGATATCGGGAGGAAC
ACCAGTGGCGAAGGCGGCCTACTGGGCACCAACTGACGCTGAGGCTCGAAAGTGTG
GGTAGCAAACAGGATTAGATACCCTGGTAGTCCACACCGTAAACGATGATTACTAGGT
GTTGGGAGATTGACCCTCTCAGTGCCGCAGTTAACACAATAAGTAATCCACCTGGGGA
GTACGACCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGCCCGCACAAGCAGTGGA
GTATGTGGTTTAATTCGACGCAACGCGAAGAACCTTACCAAGTCTTGACATCCCTTGAC
GATGCTGGAAACAGTATTTCTCTTCGGAGCAAGGAGACAGGTGGTGCATGGTTGTCGT
CAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTATGGTCA
GTTACTACGCAAGAGGACTCTGGCCAGACTGCCGTTGACAAAACGGAGGAAGGTGGG
GATGACGTCAAATCATCATGCCCTTTATGACTTGGGCTACACACGTACTACAATGGCGT
TAAACAAAGAGAAGCAAGACCGCGAGGTGGAGCAAAACTCAGAAACAACGTCCCAGTT
CGGACTGCAGGCTGCAACTCGCCTGCACGAAGTCGGAATTGCTAGTAATCGTGGATC
AGCATGCCACGGTGAATACGTTCCCGGGCCTTGTACACACCGCCCGTCACACCATGA
GAGCCGGGGGGACCCGAAGTCGGTAGTCTAACCGCAAGGAGGACGCCGCCGAAGGT
AAAACTGGTGATTGGGGTGAAGTCGTAACAAGGTAGCCGT SEQ ID
ATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGGCAGGCTTAACACATGCAA No. 16
GTCGAGGGGCAGCATAATGGTAGTAATACTATTGATGGCGACCGGCGGACGGGTGCG
TAACGCGTATGCAACCTACCCTTTACAGGGGGATAACACTGAGAAATCGGTACTAATA
CCCCATAATATTCTGGGAGGCATCTTTCGGAGTTGAAAGCTTTGGTGGTAAAGGATGG
GCATGCGTTGTATTAGCTAGTTGGTAAGGTAACGGCTTACCAAGGCGACGATACATAG
GGGGACTGAGAGGTTAACCCCCCACATTGGTACTGAGACACGGACCAAACTCCTACG
GGAGGCAGCAGTGAGGAATATTGGTCAATGGACGGAAGTCTGAACCAGCCATGCCGC
GTGCAGGAAGACGGCTCTATGAGTTGTAAACTGCTTTTGTACGAGGGTAAACGCAGAT
ACGTGTATCTGCCTGAAAGTATCGTACGAATAAGGATCGGCTAACTCCGTGCCAGCAG
CCGCGGTAATACGGAGGATCCAAGCGTTATCCGGATTTATTGGGTTTAAAGGGTGCGT
AGGCGGTTTAGTAAGTCAGCGGTGAAATTTTGGTGCTTAACACCAAACGTGCCGTTGA
TACTGCTGGGCTAGAGAGTAGTTGCGGTAGGCGGAATGTATGGTGTAGCGGTGAAAT
GCTTAGAGATCATACAGAACACCGATTGCGAAGGCAGCTTACCAAACTATATCTGACG
TTGAGGCACGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCAG
TAAACGATGATAGCTCGTTGTCGGCGATACACAGTCGGTGACTAAGAGAAATCGATAA
GCTATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGGC
CCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAACCTTACCCG
GGCTTGAAAGTTACTGACGATTCTGGAAACAGGATTTCCCTTCGGGGCAGGAAACTAG
GTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGGTTAAGTCCCATAACG
AGCGCAACCCCTACTGATAGTTGCCATCAGAGCGTTTGAGCGATCAAACAAGCTGGGC
ACTCTATCGGGACTGCCGGTGTAAGCCGAGAGGAAGGTGGGGATGACGTCAAATCAG
CACGGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGTAGGTACAGAGGGCAGC
CACCCAGTGATGGGGAGCGAATCTCGAAAGCCTATCTCAGTTCGGATTGGAGGCTGA
AACTCGCCTCCATGAAGTTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGA
ATACGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGGAGTTGGGGGTGCCT
GAAGTTCGTGACCGAAAGGAGCGACCTAGGGCAAAACCGATGACTGGGGCTAAGTCG
TAACAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ ID
TTTAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 17
GTCGAACGGAGTTATTTTGGAAATCTCTTCGGAGATGGAATTCATAACTTAGTGGCGG
ACGGGTGAGTAACGCGTGAGCAATCTGCCCTTAGGTGGGGGATAACAGCCGGAAACG
GCTGCTAATACCGCATAACACATTGAAGCCGCATGGTTTTGATGTCAAAGATTTATTGC
CTTTGGATGAGCTCGCGTCTGATTAGCTGGTTGGCGGGGTAACGGCCCACCAAGGCG
ACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCC
AGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGC
AGCAACGCCGCGTGATTGAAGAAGGCCTTCGGGTTGTAAAGATCTTTAATTGGGGACG
AAAAATGACGGTACCCAAAGAATAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGGT
AATACGTAGGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGCGAGTAGGCGG
GCTGGCAAGTTGGGAGTGAAATCCCGGGGCTTAACCCCGGAACTGCTTTCAAAACTG
CTGGTCTTGAGTGATGGAGAGGCAGGCGGAATTCCGTGTGTAGCGGTGAAATGCGTA
GATATACGGAGGAACACCAGTGGCGAAGGCGGCCTGCTGGACATTAACTGACGCTGA
GGAGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAAA
CGATGGATACTAGGTGTGGGAGGTATTGACCCCTTCCGTGCCGGAGTTAACACAATAA
GTATCCCACCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGGC
CCGCACAAGCAGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAGG
TCTTGACATCCCTCTGACCGCCCTAGAGATAGGGTTTCCCTTCGGGGCAGAGGTGACA
GGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAAC
GAGCGCAACCCTTACGGTTAGTTGATACGCAAGATCACTCTAGCCGGACTGCCGTTGA
CAAAACGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGACCTGGGCT
ACACACGTACTACAATGGCAGTCATACAGAGGGAAGCAAAACAGTGATGTGGAGCAAA
TCCCTAAAAGCTGTCCCAGTTCAGATTGCAGGCTGCAACTCGCCTGCATGAAGTCGGA
ATTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACAC
ACCGCCCGTCACACCATGAGAGCCGGTAATACCCGAAGTCCGTAGCCTAACCGCAAG
GAGGGCGCGGCCGAAGGTAGGACTGGTAATTAGGGTGAAGTCGTAACAAGGTAGCC
GTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
ACGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA No. 18
GTCGAACGGTTAAGGCGCCTTCGGGCGCGAATAGAGTGGCGAACGGGTGAGTAACAC
GTGACCAACCTGCCCCCCTCCCCGGGATAACGCGAGGAAACCCGCGCTAATACCGGA
TACTCCGCCCCTCCCGCATGGGAGGGGCGGGAAAGCCCCGACGGAGGGGGATGGG
GTCGCGGCCCATTAGGTAGACGGCGAGGCAACGGCCCACCGTGCCTGCGATGGGTA
GCCGGGTTGAGAGACCGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTAC
GGGAGGCAGCAGTGGGGAATTTTGCGCAATGGGGGGAACCCTGACGCAGCAACGCC
GCGTGCGGGACGAAGGCCTTCGGGTTGTAAACCGCTTTCAGCAGGGAAGAAGTTGAC
GGTACCTGCAGAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAG
GGGGCGAGCGTTATCCGGATTCATTGGGCGTAAAGCGCGCGTAGGCGGCCCGTCAA
GGGGAACCTCTAACCCGAGGGCTCAACCCCCGGCCGGGTTCCGAACTGGCAGGCTC
GAGTTTGGTAGAGGAAGATGGAATTCCCGGTGTAGCGGTGGAATGCGCAGATATCGG
GAAGAACACCGATGGCGAAGGCAGTCTTCTGGGCCATCAACTGACGCTGAGGCGCGA
AAGCTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCCAGCCGTAAACGATGGG
TGCTAGGTGTGGGGGGATCATCCCTCCGTGCCGCAGCCAACGCATTAAGCACCCCGC
CTGGGGAGTACGGCCGCAAGGCTAAAACTCAAAGGAATTGACGGGGGCCCGCACAA
GCAGCGGAGCATGTGGCTTAATTCGAAGCAACGCGAAGAACCTTACCAGGGCTTGAC
ATGCTGGTGAAGCCGGGGAAACCCGGTGGCCGAGAGGAGCCAGCGCAGGTGGTGCA
TGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAAC
CCCTGCCATATGTTGCCAGCATTCAGTTGGGGACTCATATGGGACTGCCGGCGTCAA
GCCGGAGGAAGGTGGGGACGACGTCAAGTCATCATGCCCTTTATGCCCTGGGCTGCA
CACGTGCTACAATGGCCGGTACAACGGGCCGCGACCTGGCGACAGGAAGCGAATCC
CTCAAAGCCGGCCCCAGTTCGGATCGGAGGCTGCAACCCGCCTCCGTGAAGTCGGA
GTTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACA
CACCGCCCGTCACACCACCCGAGTCGTCTGCACCCGAAGCCGCCGGCCGAACCCGC
AAGGGGCGGAGGCGTCGAAGGTGTGGAGGGTAAGGGGGGTGAAGTCGTAACAAGGT
AGCCGTACCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 19
GTCGAGCGAAGCACTTGCCATTGACTCTTCGGAAGATTTGGCATTTGACTGAGCGGCG
GACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGAATAACAGTTAGAAAT
GGCTGCTAATGCCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTGAGG
TGGTATGAGATGGGCCCGCGTCTGATTAGGTAGTTGGCGGGGTAACGGCCCACCAAG
CCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACG
GCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTG
ATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGG
GAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGC
GGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGA
CGGACGGGCAAGTCTGATGTGAAAGCCCGGGGCTTAACCCCGGGACTGCATTGGAAA
CTGTCCATCTTGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGT
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGTTGCAAAGCAATCCGGTGCCGCAGCAAACGCAG
TAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGG
ACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCA
AGTCTTGACATCTGCCTGACCGTTCCTTAACCGGAACTTTCCTTCGGGACAGGCAAGA
CAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCA
ACGAGCGCAACCCCTGTCCTTAGTAGCCAGCAGTCCGGCTGGGCACTCTAGGGAGAC
TGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATG
ATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGTGGTGACAC
TGAGCAAATCTCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCAC
GAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGT
CTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCT
AACCGCAAGGGAGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAAC
AAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TTATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA No. 20
GTCGAACGAAGCATTTAAGACGGATTCTTTCGGGATGAAGACTTTTATGACTGAGTGG
CGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCACACAGGGGGATAGCAGTTGGAA
ACGGCTGATAATACCGCATAAGCGCACAGTACCGCATGGTACAGTGTGAAAAACTCCG
GTGGTGTGAGATGGACCCGCGTCTGATTAGCTTGTTGGCAGGGTAACGGCCTACCAA
GGCAACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACAC
GGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCT
GATGCAGCGACGCCGCGTGAGTGAAGAAGTAATTCGTTATGTAAAGCTCTATCAGCAG
GGAAGATAGTGACGGTACCTGACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCG
CGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGG
TGGCATCACAAGTCAGAAGTGAAAGCCCGGGGCTCAACCCCGGGACTGCTTTTGAAA
CTGTGGAGCTGGAGTGCAGGAGAGGCAAGTGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTGCTGGACTGTAACTGACAC
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGGCTCATAAGAGCTICGGTGCCGCAGCAAACGCA
ATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGG
GACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTAC
CAAGTCTTGACATCCTCTTGCCCGGTCAGTAATGTGACCTTTTCTTCGGAACAAGAGTG
ACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGC
AACGAGCGCAACCCCTATTCTTAGTAGCCAGCATATAAGGTGGGCACTCTAGGAAGAC
TGCCAGGGATAACCTGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATG
ACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGTGAAGCGAGAGTGTGAGCTT
AAGCAAATCACAAAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGA
AGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCT
TGTACACACCGCCCGTCACACCATGGGAGTCGGAAATGCCCGAAGTCGGTGACCTAA
CGAAAGAAGGAGCCGCCGAAGGCAGGTCTGATAACTGGGGTGAAGTCGTAACAAGGT
AGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
AGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAAGT NO. 21
CGAACGGAGTTATGCAGAGGAAGTTTTCGGATGGAATCGGCGTAACTTAGTGGCGGA
CGGGTGAGTAACGCGTGGGAAACCTGCCCTGTACCGGGGGATAACACTTAGAAATAG
GTGCTAATACCGCATAAGCGCACAGCTTCACATGARGCAGTGTGAAAAACTCCGGTGG
TACAGGATGGTCCCGCGTCTGATTAGCCAGTTGGCAGGGTAAYGGCCTACCAAAGCG
ACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCC
CAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGATG
CAGCGACGCCGCGTGAGTGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGGGAA
GAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGT
AATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGACGG
CATGACAAGCCAGATGTGAAAACCCAGGGCTCAACCCTGGGACTGCATTTGGAACTG
CCAGGCTGGAGTGCAGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGCGTA
GATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACTGTAACTGACGTTGA
GGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCGGTAAA
CGATGATTGCTAGGTGTAGGTGGGTATGGACCCATCGGTGCCGCAGCTAACGCAATA
AGCAATCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGA
CCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAA
GTCTTGACATCCCAATGACGTGTCCGTAACGGGGCATTCTCTTCGGAGCATTGGAGAC
AGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAA
CGAGCGCAACCCTTATCCTTAGTAGCCAGCAGGTARAGCTGGGCACTCTAGGGAGAC
TGCCGGGGATAACCCGGAGGAAGGCGGGGAYGACGTCAAATCATCATGCCCCTTATG
ATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGTGATGTT
GAGCAAATCCCAGAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATG
AAGCTGGAATCGCTAGTAATCGCGAATCAGCATGTCGCGGTGAATACGTTCCCGGGTC
TTGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGCCTGTGACCTAA
CCGCAAGGGAGGAGCAGTCGAAGGCAGGTCTAATAACTGGGGTGAAGTCGTAACAAG
GTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TTTAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA NO. 22
GTCGAACGGAGTTATTTTGGAAATCTCTTCGGGGATGGAATTCATAACTTAGTGGCGG
ACGGGTGAGTAACGCGTGAGCAATCTGCCCTTAGGTGGGGGATAACAGCCGGAAACG
GCTGCTAATACCGCATAACACATTGAAGCCGCATGGTTTTGATGTCAAAGATTTATTGC
CTTTGGATGAGCTCGCGTCTGATTAGCTGGTTGGCGGGGTAACGGCCCACCAAGGCG
ACGATCAGTAGCCGGACTGAGAGGTTGAACGGCCACATTGGGACTGAGACACGGCCC
AGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCGCAATGGGGGAAACCCTGACGC
AGCAACGCCGCGTGATTGAAGAAGGCCTTCGGGTTGTAAAGATCTTTAATTGGGGACG
AAWWWTGACGGTACCCAAAGAATAAGCTCCGGCTAACTACGTGCCAGCAGCCGCGG
TAATACGTAGGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGCGAGTAGGCG
GGCTGGCAAGTTGGGAGTGAAATCCCGGGGCTTAACCCCGGAACTGCTTTCAAAACT
GCTGGTCTTGAGTGATGGAGAGGCAGGCGGAATTCCGTGTGTAGCGGTGAAATGCGT
AGATATACGGAGGAACACCAGTGGCGAAGGCGGCCTGCTGGACATTAACTGACGCTG
AGGAGCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGTAA
ACGATGGATACTAGGTGTGGGAGGTATTGACCCCTTCCGTGCCGGAGTTAACACAATA
AGTATCCCACCTGGGGAGTACGGCCGCAAGGTTGAAACTCAAAGGAATTGACGGGGG
CCCGCACAAGCAGIGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAG
GTCTTGACATCCCTCTGACCGCCCTAGAGATAGGGTTTCCCTTCGGGGCAGAGGTGA
CAGGTGGTGCATGGITGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCA
ACGAGCGCAACCCTTACGGTTAGTTGATACGAAAGATCACTCTAGCCGGACTGCCGTT
GACAAAACGGAGGAAGGTGGGGACGACGTCAAATCATCATGCCCCTTATGACCTGGG
CTACACACGTACTACAATGGCAGTCATACAGAGGGAAGCAAAACAGTGATGTGGAGCA
AATCCCTAAAAGCTGTCCCAGTTCAGATTGCAGGCTGCAACTCGCCTGCATGAAGTCG
GAATTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTAC
ACACCGCCCGTCACACCATGAGAGCCGGTAATACCCGAAGTCCGTAGCCTAACCGCA
AGGAGGGCGCGGCCGAAGGTAGGACTGGTAATTAGGGTGAAGTCGTAACAAGGTAGC
CGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
ACGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCCTAACACATGCAA NO. 23
GTCGAACGGTTAAGGCGCCTTCGGGCGCGAATAGAGTGGCGAACGGGTGAGTAACAC
GTGACCAACCTGCCCCCCTCCCCGGGATAACGCGAGGAAACCCGCGCTAATACCGGA
TACTCCGCCCCTCCCGCATGGGAGGGGCGGGAAAGCCCCGACGGAGGGGGATGGG
GTCGCGGCCCATTAGGTAGACGGCGGGGCAACGGCCCACCGTGCCTGCGATGGGTA
GCCGGGTTGAGAGACCGACCGGCCACATTGGGACTGAGATACGGCCCAGACTCCTAC
GGGAGGCAGCAGTGGGGAATTTTGCGCAATGGGGGGAACCCTGACGCAGCAACGCC
GCGTGCGGGACGAAGGCCTTCGGGTTGTAAACCGCTTTCAGCAGGGAAGAAGTTGAC
GGTACCTGCAGAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAG
GGGGCGAGCGTTATCCGGATTCATTGGGCGTAAAGCGCGCGTAGGCGGCCCGTCAA
GCGGAACCTCTAACCCGAGGGCTCAACCCCCGGCCGGGTTCCGAACTGGCAGGCTC
GAGTTTGGTAGAGGAAGATGGAATTCCCGGTGTAGCGGTGGAATGCGCAGATATCGG
GAAGAACACCGATGGCGAAGGCAGTCTTCTGGGCCATCAACTGACGCTGAGGCGCGA
AAGCTGGGGGAGCGAACAGGATTAGATACCCTGGTAGTCCCAGCCGTAAACGATGGG
YGCTAGGTGTGGGGGGATCATCCCTCCGTGCCGCAGCCAACGCATTAAGCRCCCCGC
CTGGGGAGTACGGCCGCAAGGCTAAAACTCAAAGGAATTGACGGGGGCCCGCACAA
GCAGCGGAGCATGTGGCTTAATTCGAAGCAACGCGAAGAACCTTACCAGGGCTTGAC
ATGCTGGTGAAGCCGGGGAAACCCGGTGGCCGAGAGGAGCCAGCGCAGGTGGTGCA
TGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAAC
CCCTGCCATATGTTGCCAGCATTCAGTTGGGGACTCATATGGGACTGCCGGCGTCAA
GCCGGAGGAAGGTGGGGACGACGTCAAGTCATCATGCCCTTTATGCCCTGGGCTGCA
CACGTGCTACAATGGCCGGTACAACGGGCCGCGACCTGGCGACAGGAAGCGAATCC
CTCAAAGCCGGCCCCAGTTCGGATCGGAGGCTGCAACCCGCCTCCGTGAAGTCGGA
GTTGCTAGTAATCGCGGATCAGCATGCCGCGGTGAATACGTTCCCGGGCCTTGTACA
CACCGCCCGTCACACCACCCGAGTCGTCTGCACCCGAAGCCGCCGGCCGAACCCGC
AAGGGGCGGAGGCGTCGAAGGTGTGGAGGGTAAGGGGGGTGAAGTCGTAACAAGGT
AGCCGTACCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
ATGGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCATGCCTAATACATGCAAG NO. 24
TCGAACGAAGTOTTTAGGAAGCTTGCTTCCAAAGAGACTTAGTGGCGAACGGGTGAGT
AACACGTAGGTAACCTGCCCATGTGCCCGGGATAACTGCTGGAAACGGTAGCTAAAAC
CGGATAGGTATGAGGGAGGCATCTTCCTCATATTAAAGCACCTTCGGGTGTGAACATG
GATGGACCTGCGGCGCATTAGCTGGTTGGTGAGGTAACGGCCCACCAAGGCGATGAT
GCGTAGCCGACCTGAGAGGGTGAACGGCCACATTGGGACTGAGACACGGCCCAAACT
CCTACGGGAGGCAGCAGTAGGGAATTTTCGTCAATGGGGGGAACCCTGAACGAGCAA
TGCCGCGTGTGTGAAGAAGGTOTTCGGATCGTAAAGCACTGTTGTAAGTGAAGAATGC
CATATAGAGGAAATGCTATGTGGGTGACGGTAGCTTACCAGAAAGCCACGGCTAACTA
CGTGCCAGCAGCCGCGGTAATACGTAGGTGGCAAGCGTTATCCGGAATCATTGGGCG
TAAAGGGTGCGTAGGTGGCACGATAAGTCTGAAGTAAAAGGCAACAGCTCAACTGTTG
TATGCTTTGGAAACTGTCGAGCTAGAGTGCAGAAGAGGGCGATGGAATTCCATGTGTA
GCGGTAAAATGCGTAGATATATGGAGGAACACCAGTGGCGAAGGCGGTCGCCTGGTC
TGTAACTGACACTGATGCACGAAAGCGTGGGGAGCAAATAGGATTAGATACCCTAGTA
GTCCACGCCGTAAACGATGAGAACTAAGTGTTGGAGAGATTCAGTGCTGCAGTTAACG
CAATAAGTTCTCCGCCTGGGGAGTATGCACGCAAGTGTGAAACTCAAAGGAATTGACG
GGGGCCCGCACAAGCGGTGGAGTATGTGGTTTAATTCGAAGCAACGCGAAGAACCTT
ACCAGGCCTTGACATGGATATAAATGTTCTAGAGATAGAAAGATAGCTATATATCACAC
AGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAA
CGAGCGCAACCCTTGTCTTCTGTTACCAGCATTAAGTTGGGGACTCAGGAGAGACTGC
CGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATGGCC
TGGGCTACACACGTACTACAATGGCGCCTACAAAGAGCAGCGACACCGCGAGGTGGA
GCGAATCTCATAAAGGGCGTCTCAGTTCGGATTGAAGTCTGCAACTCGACTTCATGAA
GTCGGAATCGCTAGTAATCGCAGATCAGCATGCTGCGGTGAATACGTTCTCGGGCCTT
GTACACACCGCCCGTCAAACCATGGGAGTTGGTAATACCCGAAGCCGGTGGCATAAC
CGCAAGGAGTGAGCCGTCGAAGGTAGGACCGATGACTGGGGTTAAGTCGTAACAAGG
TATCCCTACGGGAACGTGGGGATGGATCACCTCCTTT SEQ ID
TCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA NO. 25
GTCGAGCGAAGCRCTTRARYGGATCTCTTCGGATTGAARYTTWTKTGACTGAGCGGC
GGACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTAGAAA
TGGCTGCTAATACCGCATAAGCGCACAGGACCGCATGGTCTGGTGTGAAAAACTCCG
GTGGTATGAGATGGACCCGCGTCTGATTAGCTAGTTGGAGGGGTAACGGCCCACCAA
GGCGACGATCAGTAGCCGGCCTGAGAGGGTGAACGGCCACATTGGGACTGAGACAC
GGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCT
GATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAG
GGAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCG
CGGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAG
ACGGAAGAGCAAGTCTGATGTGAAAGGCTGGGGCTTAACCCCAGGACTGCATTGGAA
ACTGTTTTTCTAGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGT
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGTGGCAAAGCCATTCGGTGCCGCAGCAAACGCAA
TAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGG
ACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCA
AGTCTTGACATCCCTCTGACCGGCCCGTAACGGGGCCTTCCCTTCGGGGCAGAGGAG
ACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGC
AACGAGCGCAACCCCTATCCTTAGTAGCCAGCAGGTRRAGCTGGGCACTCTAGGGAG
ACTGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTA
TGATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGAGACAGCGAT
GTTGAGCAAATCCCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGC
ACGAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGG
GTCTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGAC
CCAACCTTAYAGGAGGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTA
ACAAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
CGAAGAGTTTGATCCTGGCTCAGGATGAACGCTAGCGACAGGCCTAACACATGCAAGT NO. 26
CGAGGGGCAGCGGRGAGGYAGCAATACCTTTGCCGGCGACCGGCGCACGGGTGAGT
AACACGTATGCAATCCACCTGTAACAGGGGGATAACCCGGAGAAATCCGGACTAATAC
CCCATAATATGGGCGCTCCGCATGGAGRGTCCATTAAAGAGAGCAATTTTGGTTACAG
ACGAGCATGCGCTCCATTAGCCAGTTGGCGGGGTAACGGCCCACCAAAGCGACGATG
GATAGGGGTTCTGAGAGGAAGGTCCCCCACATTGGAACTGAGACACGGTCCAAACTC
CTACGGGAGGCAGCAGTGAGGAATATTGGTCAATGGTCGGCAGACTGAACCAGCCAA
GTCGCGTGAGGGAAGACGGCCCTACGGGTTGTAAACCTCTTTTGTCGGAGAGTAAAG
TRCGCTACGTGTAGYGTATTGCAAGTATCCGAAGAAAAAGCATCGGCTAACTCCGTGC
CAGCAGCCGCGGTAATACGGAGGATGCGAGCGTTATCCGGATTTATTGGGTTTAAAG
GGTGCGTAGGCGGCACGCCAAGTCAGCGGTGAAATTTCCGGGCTCAACCCGGACTGT
GCCGTTGAAACTGGCGAGCTAGAGTGCACAAGAGGCAGGCGGAATGCGTGGTGTAG
CGGTGAAATGCATAGATATCACGCAGAACCCCGATTGCGAAGGCAGCCTGCTAGGGT
GCGACAGACGCTGAGGCACGAAAGCGTGGGTATCGAACAGGATTAGATACCCTGGTA
GTCCACGCAGTAAACGATGAATACTAACTGTTTGCGATACAATGTAAGCGGTACAGCG
AAAGCGTTAAGTATTCCACCTGGGGAGTACGCCGGCAACGGTGAAACTCAAAGGAATT
GACGGGGGCCCGCACAAGCGGAGGAACATGTGGTTTAATTCGATGATACGCGAGGAA
CCTTACCCGGGCTCAAACGCAGGGGGAATGCCGGTGAAAGTCGGCAGCTAGCAATAG
TCACCTGCGAGGTGCTGCATGGTTGTCGTCAGCTCGTGCCGTGAGGTGTCGGCTTAA
GTGCCATAACGAGCGCAACCCCTATGGACAGTTACTAACGGGTGAAGCCGAGGACTC
TGTCTAGACTGCCGGCGCAAGCCGCGAGGAAGGTGGGGATGACGTCAAATCAGCAC
GGCCCTTACGTCCGGGGCGACACACGTGTTACAATGGCAGGTACAGAAGGCAGCCAG
TCAGCAATGACGCGCGAATCCCGAAAACCTGTCTCAGTTCGGATTGGAGTCTGCAACC
CGACTCCATGAAGCTGGATTCGCTAGTAATCGCGCATCAGCCATGGCGCGGTGAATA
CGTTCCCGGGCCTTGTACACACCGCCCGTCAAGCCATGGAAGCCGGGAGTACCTGAA
GCATGCAACCGCAAGGAGCGTACGAAGGTAATACCGGTAACTGGGGCTAAGTCGTAA
CAAGGTAGCCGTACCGGAAGGTGCGGCTGGAACACCTCCTTT SEQ ID
TCAGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA NO. 27
GTCGAGCGAAGCACTTRYYATTGAMTCTTCGGARGATTTRGCATKTGACTGAGCGGCG
GACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGAATAACAGTTAGAAAT
GGCTGCTAATGCCGCATAAGCGCACAGGRCCGCATGGTCYGGTGTGAAAAACTSMGG
TGGTATGAGATGGROCCGCGTCTGATTAGGTAGTTGGCGGGGTAACGGCCCACCAAG
CCGACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACG
GCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCTG
ATGCAGCGACGCCGCGTGAAGGAAGAAGTATCTCGGTATGTAAACTTCTATCAGCAGG
GAAGAAAATGACGGTACCTGACTAAGAAGCCCCGGCTAACTACGTGCCAGCAGCCGC
GGTAATACGTAGGGGGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGTAGA
CGGACGGGCAAGTCTGATGTGAAAGCCCGGGGCTTAACCCCGGGACTGCATTGGAAA
CTGTCCATCTTGAGTGCCGGAGAGGTAAGCGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGGTAACTGACGT
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGTTGCAAAGCAATCCGGTGCCGCAGCAAACGCAG
TAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGG
ACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCA
AGTCTTGACATCTGCCTGACCGTTCCTTAACCGGAACTTTCCTTCGGGACAGGCAAGA
CAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCA
ACGAGCGCAACCCCTGTCCTTAGTAGCCAGCAGTCCGGCTGGGCACTCTAGGGAGAC
TGCCGGGGATAACCCGGAGGAAGGCGGGGACGACGTCAAATCATCATGCCCCTTATG
ATTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCGGAGTGGTGACAC
TGAGCAAATCTCAAAAATAACGTCCCAGTTCGGACTGCAGTCTGCAACTCGACTGCAC
GAAGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGT
CTTGTACACACCGCCCGTCACACCATGGGAGTCAGTAACGCCCGAAGTCAGTGACCT
AACCGCAAGGGAGGAGCTGCCGAAGGCGGGACCGATAACTGGGGTGAAGTCGTAAC
AAGGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
TTATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAA NO. 28
GTCGAACGAAGCATTTGMGACRGATTYYTTCGGRWTGAAGACTTTTATGACTGAGTGG
CGGACGGGTGAGTAACGCGTGGGTAACCTGCCTCACACAGGGGGATAGCAGTTGGAA
ACGGCTGATAATACCGCATAAGCGCACAGTACCGCATGGTACAGTGTGAAAAACTCCG
GTGGTGTGAGATGGACCCGCGTCTGATTAGCTTGTTGGCRGGGTAACGGCCYACCAA
GGCAACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACAC
GGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGAGGAAACTCT
GATGCAGCGACGCCGCGTGAGTGAAGAAGTAATTCGTTATGTAAAGCTCTATCAGCAG
GGAAGATAGTGACGGTACCTGACTAAGAAGCTCCGGCTAAATACGTGCCAGCAGCCG
CGGTAATACGTATGGAGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGTGTAGG
TGGCATCACAAGTCAGAAGTGAAAGCCCGGGGCTCAACCCCGGGACTGCTTTTGAAA
CTGTGGAGCTGGAGTGCAGGAGAGGCAAGTGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTGCTGGACTGTAACTGACAC
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGGCTCATAAGAGCTTCGGTGCCGCAGCAAACGCA
ATAAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGG
GACCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTAC
CAAGTCTTGACATCCTCTTGRCCGGTCAGTAATGTGRYCTTTTCTTCGGAACAAGAGTG
ACAGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGC
AACGAGCGCAACCCCTATTCTTAGTAGCCAGCATTTAAGRTGGGCACTCTAGGAAGAC
TGCCAGGGATAACCTGGAGGAAGGTGGGGATGACGTCAAATCATCATGCCCCTTATG
ACTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGTGAAGCGAGAGTGTGAGCTT
AAGCAAATCACAAAAATAACGTCTCAGTTCGGATTGTAGTCTGCAACTCGACTACATGA
AGCTGGAATCGCTAGTAATCGCGAATCAGAATGTCGCGGTGAATACGTTCCCGGGTCT
TGTACACACCGCCCGTCACACCATGGGAGTCGGAAATGCCCGAAGTCGGTGACCTAA
CGAAAGAAGGAGCCGCCGAAGGCAGGTCTGATAACTGGGGTGAAGTCGTAACAAGGT
AGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT SEQ ID
ATGAGAGTTTGATCCTGGCTCAGGATGAACGCTGGCGGCGTGCTTAACACATGCAAGT NO. 29
CGAACGAAGCACTCTATTTGATTTTCTTCGGRAATGAAGATTTTGTGACTGAGTGGCGG
ACGGGTGAGTAACGCGTGGGTAACCTGCCTCATACAGGGGGATAACAGTTGGAAACG
ACTGCTAATACCGCATAAGCGCACAGGATYGCATGRTCCGGTGTGAAAAACTCCGGTG
GTATGRGATGGACCCGCGTCTGATTAGCCAGTTGGCAGGGTAACGGCCTACCAAAGC
GACGATCAGTAGCCGACCTGAGAGGGTGACCGGCCACATTGGGACTGAGACACGGC
CCAAACTCCTACGGGAGGCAGCAGTGGGGAATATTGCACAATGGGGGAAACCCTGAT
GCAGCGACGCCGCGTGAGCGAAGAAGTATTTCGGTATGTAAAGCTCTATCAGCAGGG
AAGAAGAATGACGGTACCTGACTAAGAAGCACCGGCTAAATACGTGCCAGCAGCCGC
GGTAATACGTATGGTGCAAGCGTTATCCGGATTTACTGGGTGTAAAGGGAGCGCAGG
CGGTGCGGCAAGTCTGATGTGAAAGCCCGGGGCTCAACCCCGGTACTGCATTGGAAA
CTGTCGTACTAGAGTGTCGGAGGGGTAAGTGGAATTCCTAGTGTAGCGGTGAAATGC
GTAGATATTAGGAGGAACACCAGTGGCGAAGGCGGCTTACTGGACGATAACTGACGC
TGAGGCTCGAAAGCGTGGGGAGCAAACAGGATTAGATACCCTGGTAGTCCACGCCGT
AAACGATGAATACTAGGTGTCGGGGAGCATTGCTCTTCGGTGCCGCAGCAAACGCAAT
AAGTATTCCACCTGGGGAGTACGTTCGCAAGAATGAAACTCAAAGGAATTGACGGGGA
CCCGCACAAGCGGTGGAGCATGTGGTTTAATTCGAAGCAACGCGAAGAACCTTACCAA
GTCTTGACATCCCGATGACAGAGTATGTAATGTASYYTCYCTTCGGRGCATCGGTGAC
AGGTGGTGCATGGTTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAA
CGAGCGCAACCCCTGTYCTTAGTAGCCAGCGGTTCGGCCGGGCACTCTAGGGAGACT
GCCAGGGATAACCTGGAGGAAGGCGGGGATGACGTCAAATCATCATGCCCCTTATGA
CTTGGGCTACACACGTGCTACAATGGCGTAAACAAAGGGAAGCRRAGCCGTGAGGCC
GAGCAAATCTCAAAAATAACGTCTCAGTTCGGACTGTAGTCTGCAACCCGACTACACG
AAGCTGGAATCGCTAGTAATCGCAGATCAGAATGCTGCGGTGAATACGTTCCCGGGTC
TTGTACACACCGCCCGTCACACCATGGGAGTTGGAAATGCCCGAAGTCAGTGACCCA
ACCGCAAGGAGGGAGCTGCCGAAGGCAGGTTCGATAACTGGGGTGAAGTCGTAACAA
GGTAGCCGTATCGGAAGGTGCGGCTGGATCACCTCCTTT
TABLE-US-00003 TABLE 3 16S rDNA sequence Consortium No Taxonomy
identifier 1 2 3 4 5 6 7 8 9 10 B1 Eisenbergiella sp. SEQ ID No. 1
X X X X X X X X X X B2 Butyricicoccus sp. SEQ ID No. 2 X X X X X X
X X X B3 Clostridiales sp. SEQ ID No. 3 X X X X X B4 Alistipes
obesi SEQ ID No. 4 X X B5 Alistipes indistinctus SEQ ID No. 5 X X X
B6 Gordonibacter SEQ ID No. 6 X X X X urolithinfaciens B7
Faecalitalea sp. SEQ ID No. 7 X X X X X X X X X B8 Blautia sp. SEQ
ID No. 8 X X X X X B9 Barnesiella SEQ ID No. 9 X X X X X X X
intestinihominis B10 Alistipes timonensis SEQ ID No. 10 X X B11
Blautia sp. SEQ ID No. 11 X X X X B12 Lachnospira sp. SEQ ID No. 12
X X B13 Ruminococcus callidus SEQ ID No. 13 X X X X X B14 Roseburia
faecis SEQ ID No. 14 X X X X B15 Faecaiibacterium SEQ ID No. 15 X X
prausnitzii B4 Alistipes obesi SEQ ID No. 16 X X B2 Butyricicoccus
sp. SEQ ID No. 17 X B6 Gordonibaoter SEQ ID No. 18 X X X
urolithinfaciens B11 Blautia sp. SEQ ID No. 19 X X B12 Lachnospira
sp. SEQ ID No. 20 X X Number of bacteria 15 9 12 9 9 9 6 3 2 9
SEQUENCE LISTINGS
1
3111527DNAEisenbergiella sp. 1agagagtttg atcctggctc aggatgaacg
ctggcggcgt gcctaacaca tgcaagtcga 60acggagttat gcagaggaag ttttcggatg
gaatcggcgt aacttagtgg cggacgggtg 120agtaacgcgt gggaaacctg
ccctgtaccg ggggataaca cttagaaata ggtgctaata 180ccgcataagc
gcacagcttc acatgaggca gtgtgaaaaa ctccggtggt acaggatggt
240cccgcgtctg attagccagt tggcagggta acggcctacc aaagcgacga
tcagtagccg 300gcctgagagg gtgaacggcc acattgggac tgagacacgg
cccaaactcc tacgggaggc 360agcagtgggg aatattgcac aatgggggaa
accctgatgc agcgacgccg cgtgagtgaa 420gaagtatttc ggtatgtaaa
gctctatcag cagggaagaa aatgacggta cctgactaag 480aagccccggc
taactacgtg ccagcagccg cggtaatacg tagggggcaa gcgttatccg
540gatttactgg gtgtaaaggg agcgtagacg gcatgacaag ccagatgtga
aaacccaggg 600ctcaaccctg ggactgcatt tggaactgcc aggctggagt
gcaggagagg taagcggaat 660tcctagtgta gcggtgaaat gcgtagatat
taggaggaac accagtggcg aaggcggctt 720actggactgt aactgacgtt
gaggctcgaa agcgtgggga gcaaacagga ttagataccc 780tggtagtcca
cgcggtaaac gatgattgct aggtgtaggt gggtatggac ccatcggtgc
840cgcagctaac gcaataagca atccacctgg ggagtacgtt cgcaagaatg
aaactcaaag 900gaattgacgg ggacccgcac aagcggtgga gcatgtggtt
taattcgaag caacgcgaag 960aaccttacca agtcttgaca tcccaatgac
gtgtccgtaa cggggcattc tcttcggagc 1020attggagaca ggtggtgcat
ggttgtcgtc agctcgtgtc gtgagatgtt gggttaagtc 1080ccgcaacgag
cgcaaccctt atccttagta gccagcaggt agagctgggc actctaggga
1140gactgccggg gataacccgg aggaaggcgg ggatgacgtc aaatcatcat
gccccttatg 1200atttgggcta cacacgtgct acaatggcgt aaacaaaggg
aagcgagaca gtgatgttga 1260gcaaatccca gaaataacgt ctcagttcgg
attgtagtct gcaactcgac tacatgaagc 1320tggaatcgct agtaatcgcg
aatcagcatg tcgcggtgaa tacgttcccg ggtcttgtac 1380acaccgcccg
tcacaccatg ggagttggaa atgcccgaag cctgtgacct aaccgcaagg
1440gaggagcagt cgaaggcagg tctaataact ggggtgaagt cgtaacaagg
tagccgtatc 1500ggaaggtgcg gctggatcac ctccttt
152721525DNAButyricicoccus sp. 2tttagagagt ttgatcctgg ctcaggatga
acgctggcgg cgtgcctaac acatgcaagt 60cgaacggagt tattttggaa atctcttcgg
ggatggaatt cataacttag tggcggacgg 120gtgagtaacg cgtgagcaat
ctgcccttag gtgggggata acagccggaa acggctgcta 180ataccgcata
acacattgaa gccgcatggt tttgatgtca aagatttatt gcctttggat
240gagctcgcgt ctgattagct ggttggcggg gtaacggccc accaaggcga
cgatcagtag 300ccggactgag aggttgaacg gccacattgg gactgagaca
cggcccagac tcctacggga 360ggcagcagtg gggaatattg cgcaatgggg
gaaaccctga cgcagcaacg ccgcgtgatt 420gaagaaggcc ttcgggttgt
aaagatcttt aattggggac gaattttgac ggtacccaaa 480gaataagctc
cggctaacta cgtgccagca gccgcggtaa tacgtaggga gcaagcgtta
540tccggattta ctgggtgtaa agggcgagta ggcgggctgg caagttggga
gtgaaatccc 600ggggcttaac cccggaactg ctttcaaaac tgctggtctt
gagtgatgga gaggcaggcg 660gaattccgtg tgtagcggtg aaatgcgtag
atatacggag gaacaccagt ggcgaaggcg 720gcctgctgga cattaactga
cgctgaggag cgaaagcgtg gggagcaaac aggattagat 780accctggtag
tccacgccgt aaacgatgga tactaggtgt gggaggtatt gaccccttcc
840gtgccggagt taacacaata agtatcccac ctggggagta cggccgcaag
gttgaaactc 900aaaggaattg acgggggccc gcacaagcag tggagtatgt
ggtttaattc gaagcaacgc 960gaagaacctt accaggtctt gacatccctc
tgaccgccct agagataggg tttcccttcg 1020gggcagaggt gacaggtggt
gcatggttgt cgtcagctcg tgtcgtgaga tgttgggtta 1080agtcccgcaa
cgagcgcaac ccttacggtt agttgatacg aaagatcact ctagccggac
1140tgccgttgac aaaacggagg aaggtgggga cgacgtcaaa tcatcatgcc
ccttatgacc 1200tgggctacac acgtactaca atggcagtca tacagaggga
agcaaaacag tgatgtggag 1260caaatcccta aaagctgtcc cagttcagat
tgcaggctgc aactcgcctg catgaagtcg 1320gaattgctag taatcgcgga
tcagcatgcc gcggtgaata cgttcccggg ccttgtacac 1380accgcccgtc
acaccatgag agccggtaat acccgaagtc cgtagcctaa ccgcaaggag
1440ggcgcggccg aaggtaggac tggtaattag ggtgaagtcg taacaaggta
gccgtatcgg 1500aaggtgcggc tggatcacct ccttt
152531527DNAClostridiales sp. 3tttaagagtt tgatcctggc tcaggacgaa
cgctggcggc gtgcctaaca catgcaagtc 60gaacgaagct tgatttctga ttttttcgga
atgacgaatg atatgactga gtggcggacg 120ggtgagtaac gcgtgagcaa
cctgcccttc ggaacgggat agtgtctgga aacggacagt 180aataccgtat
aatatatatt gatcgcatgg ttgatatatc aaaactgagg tgccgaagga
240tgggctcgcg tctgattaga tagttggtgg ggtaacggcc taccaagtcg
acgatcagta 300gccggactga gaggttgaac ggccacattg ggactgagac
acggcccaga ctcctacggg 360aggcagcagt ggggaatatt gcacaatggg
ggaaaccctg atgcagcaac gccgcgtgaa 420ggaagacggt tttcggattg
taaacttctg ttcttagtga agaataatga cggtagctaa 480ggagcaagcc
acggctaact acgtgccagc agccgcggta atacgtaggt ggcaagcgtt
540gtccggaatt actgggtgta aagggagcgt aggcgggatg ccaagtcagc
tgtgaaaact 600atgggcttaa cttgtagact gcagttgaaa ctggtattct
tgagtgaagt agaggttggc 660ggaattccga gtgtagcggt gaaatgcgta
gatattcgga ggaacaccgg tggcgaaggc 720ggccaactgg gctttaactg
acgctgaggc tcgaaagtgt ggggagcaaa caggattaga 780taccctggta
gtccacactg taaacgatga taactaggtg tggggggtct gaccccttcc
840gtgccgcagc taacgcaata agttatccac ctggggagta cgaccgcaag
gttgaaactc 900aaaggaattg acggggaccc gcacaagcag tggattatgt
ggtttaattc gaagcaacgc 960gaagaacctt accagcactt gacatccgac
taacgaagta gagatacatt aggtgccctt 1020cggggaaagt cgagacaggt
ggtgcatggt tgtcgtcagc tcgtgtcgtg agatgttggg 1080ttaagtcccg
caacgagcgc aacccctgcc attagttgct acgcaagagc actctaatgg
1140gaccgctacc gacaaggtgg aggaaggtgg ggacgacgtc aaatcatcat
gccccttatg 1200tgctgggcta cacacgtaat acaatggcca tcaacaaaga
gaagcaatac cgcgaggtgg 1260agcaaaacta taaaaatggt ctcagttcgg
actgcaggct gcaacccgcc tgcacgaagt 1320tggaattgct agtaatcgtg
gatcagcatg ccacggtgaa tacgttcccg ggtcttgtac 1380acaccgcccg
tcacaccatg ggagttggta acacccgaag tcagtagtct aaccgcaagg
1440aggacgctgc cgaaggtggg attgacgact ggggtgaagt cgtaacaagg
tagccgtatc 1500agaaggtgcg gctggatcac ctccttt 152741539DNAAlistipes
obesi 4atggagagtt tgatcctggc tcaggatgaa cgctagcggc aggcttaaca
catgcaagtc 60gaggggcagc ataatggtag caatactatt gatggcgacc ggcggacggg
tgcgtaacgc 120gtatgcaacc taccctttac agggggataa cactgagaaa
tcggtactaa taccccataa 180tattctggga ggcatctttc ggagttgaaa
gctttggtgg taaaggatgg gcatgcgttg 240tattagctag ttggtaaggt
aacggcttac caaggcgacg atacataggg ggactgagag 300gttaaccccc
cacattggta ctgagacacg gaccaaactc ctacgggagg cagcagtgag
360gaatattggt caatggacgg aagtctgaac cagccatgcc gcgtgcagga
agacggctct 420atgagttgta aactgctttt gtacgagggt aaacgcagat
acgtgtatct gcctgaaagt 480atcgtacgaa taaggatcgg ctaactccgt
gccagcagcc gcggtaatac ggaggatcca 540agcgttatcc ggatttattg
ggtttaaagg gtgcgtaggc ggtttagtaa gtcagcggtg 600aaattttggt
gcttaacacc aaacgtgccg ttgatactgc tgggctagag agtagttgcg
660gtaggcggaa tgtatggtgt agcggtgaaa tgcttagaga tcatacagaa
caccgattgc 720gaaggcagct taccaaacta tatctgacgt tgaggcacga
aagcgtgggg agcaaacagg 780attagatacc ctggtagtcc acgcagtaaa
cgatgatagc tcgttgtcgg cgatacacag 840tcggtgacta agagaaatcg
ataagctatc cacctgggga gtacgttcgc aagaatgaaa 900ctcaaaggaa
ttgacggggg cccgcacaag cggaggaaca tgtggtttaa ttcgatgata
960cgcgaggaac cttacccggg cttgaaagtt actgacgatt ctggaaacag
gatttccctt 1020cggggcagga aactaggtgc tgcatggttg tcgtcagctc
gtgccgtgag gtgtcgggtt 1080aagtcccata acgagcgcaa cccctactga
tagttgccat cagagcgttt gagcgatcaa 1140acaagctggg cactctatcg
ggactgccgg tgtaagccga gaggaaggtg gggatgacgt 1200caaatcagca
cggcccttac gtccggggcg acacacgtgt tacaatggta ggtacagagg
1260gcagccaccc agtgatgggg agcgaatctc gaaagcctat ctcagttcgg
attggaggct 1320gaaactcgcc tccatgaagt tggattcgct agtaatcgcg
catcagccat ggcgcggtga 1380atacgttccc gggccttgta cacaccgccc
gtcaagccat gggagttggg ggtgcctgaa 1440gttcgtgacc gaaaggagcg
acctagggca aaaccgatga ctggggctaa gtcgtaacaa 1500ggtagccgta
ccggaaggtg cggctggaac acctccttt 153951525DNAAlistipes indistinctus
5atggagagtt tgatcctggc tcaggataaa cgctagcggc aggcctaaca catgcaagtc
60gaggggcagc gggtggagta tttcggtact cctgccggcg accggcgcac gggtgcgtaa
120cgcgtatgca acctaccttt aacaggggga taatccgaag aaatttggtc
taatacccca 180taatatcatt taaggcatct tagatggttg aaaattccga
tggttagaga tgggcatgcg 240ttgtattagc tagttggtga ggtaacggct
caccaaggct acgatacata gggggactga 300gaggttttcc ccccacactg
gtactgagac acggaccaga ctcctacggg aggcagcagt 360gaggaatatt
ggtcaatgga cgcaagtctg aaccagccat gccgcgtgca ggatgaaggt
420gctatgcatt gtaaactgct tttgtacgag ggtaaatgca ggtacgtgta
cctgtttgaa 480agtatcgtac gaataagggt cggctaactc cgtgccagca
gccgcggtaa tacggaggac 540ccgagcgtta tccggattta ttgggtttaa
agggtgcgta ggcggattag taagttagag 600gtgaaagctc gatgctcaac
atcgaaattg cctctgatac tgttagtcta gagtatagtt 660gcggaaggcg
gaatgtgtgg tgtagcggtg aaatgcttag atatcacaca gaacaccgat
720tgcgaaggca gctttccaag ctattactga cgctgatgca cgaaagcgtg
gggagcgaac 780aggattagat accctggtag tccacgccgt aaacgatgat
aactcgttgc aggcgataca 840cagtctgtga cttagcgaaa gcgttaagtt
atccacctgg ggagtacgtt cgcaagaatg 900aaactcaaag gaattgacgg
gggcccgcac aagcggagga acatgtggtt taattcgatg 960atacgcgagg
aaccttaccc gggcttgaaa gttagcgacg gatcctgaaa ggggtcttct
1020cttcggagcg cgaaactagg tgctgcatgg ttgtcgtcag ctcgtgccgt
gaggtgtcgg 1080gttaagtccc ataacgagcg caacccctac tgttagttac
cagcacgtca aggtgggcac 1140tctagcagga ctgccggtgt aagccgagag
gaaggtgggg atgacgtcaa atcagcacgg 1200cccttacgtc cggggcgaca
cacgtgttac aatggtcggt acagagggtc gctaccccgt 1260gaggggatgc
caatctcgaa agccgatctc agttcggatt ggaggctgaa actcgcctcc
1320atgaagttgg attcgctagt aatcgcgcat cagccatggc gcggtgaata
cgttcccggg 1380ccttgtacac accgcccgtc aagccatggg agttgggggt
gcctgaagta cgtgaccgca 1440aggagcgtcc tagggcaaaa ccgatgactg
gggctaagtc gtaacaaggt agccgtaccg 1500gaaggtgcgg ctggaacacc tcctt
152561506DNAGordonibacter urolithinfaciens 6acggagagtt tgatcctggc
tcaggatgaa cgctggcggc gtgcctaaca catgcaagtc 60gaacggttaa ggcgccttcg
ggcgcgaata gagtggcgaa cgggtgagta acacgtgacc 120aacctgcccc
cctccccggg ataacgcgag gaaacccgcg ctaataccgg atactccgcc
180cctcccgcat gggaggggcg ggaaagcccc gacggagggg gatggggtcg
cggcccatta 240ggtagacggc ggggcaacgg cccaccgtgc ctgcgatggg
tagccgggtt gagagaccga 300ccggccacat tgggactgag atacggccca
gactcctacg ggaggcagca gtggggaatt 360ttgcgcaatg gggggaaccc
tgacgcagca acgccgcgtg cgggacgaag gccttcgggt 420tgtaaaccgc
tttcagcagg gaagaagttg acggtacctg cagaagaagc cccggctaac
480tacgtgccag cagccgcggt aatacgtagg gggcgagcgt tatccggatt
cattgggcgt 540aaagcgcgcg taggcggccc gtcaagcgga acctctaacc
cgagggctca acccccggcc 600gggttccgaa ctggcaggct cgagtttggt
agaggaagat ggaattcccg gtgtagcggt 660ggaatgcgca gatatcggga
agaacaccga tggcgaaggc agtcttctgg gccatcaact 720gacgctgagg
cgcgaaagct gggggagcga acaggattag ataccctggt agtcccagcc
780gtaaacgatg ggtgctaggt gtggggggat catccctccg tgccgcagcc
aacgcattaa 840gcaccccgcc tggggagtac ggccgcaagg ctaaaactca
aaggaattga cgggggcccg 900cacaagcagc ggagcatgtg gcttaattcg
aagcaacgcg aagaacctta ccagggcttg 960acatgctggt gaagccgggg
aaacccggtg gccgagagga gccagcgcag gtggtgcatg 1020gctgtcgtca
gctcgtgtcg tgagatgttg ggttaagtcc cgcaacgagc gcaacccctg
1080ccatatgttg ccagcattca gttggggact catatgggac tgccggcgtc
aagccggagg 1140aaggtgggga cgacgtcaag tcatcatgcc ctttatgccc
tgggctgcac acgtgctaca 1200atggccggta caacgggccg cgacctggcg
acaggaagcg aatccctcaa agccggcccc 1260agttcggatc ggaggctgca
acccgcctcc gtgaagtcgg agttgctagt aatcgcggat 1320cagcatgccg
cggtgaatac gttcccgggc cttgtacaca ccgcccgtca caccacccga
1380gtcgtctgca cccgaagccg ccggccgaac ccgcaagggg cggaggcgtc
gaaggtgtgg 1440agggtaaggg gggtgaagtc gtaacaaggt agccgtaccg
gaaggtgcgg ctggatcacc 1500tccttt 150671535DNAFaecalitalea sp.
7atggagagtt tgatcctggc tcaggatgaa cgctggcggc atgcctaata catgcaagtc
60gaacgaagtc tttaggaagc ttgcttccaa agagacttag tggcgaacgg gtgagtaaca
120cgtaggtaac ctgcccatgt gcccgggata actgctggaa acggtagcta
aaaccggata 180ggtatgaggg aggcatcttc ctcatattaa agcaccttcg
ggtgtgaaca tggatggacc 240tgcggcgcat tagctggttg gtgaggtaac
ggcccaccaa ggcgatgatg cgtagccgac 300ctgagagggt gaacggccac
attgggactg agacacggcc caaactccta cgggaggcag 360cagtagggaa
ttttcgtcaa tggggggaac cctgaacgag caatgccgcg tgtgtgaaga
420aggtcttcgg atcgtaaagc actgttgtaa gtgaagaatg ccatatagag
gaaatgctat 480gtgggtgacg gtagcttacc agaaagccac ggctaactac
gtgccagcag ccgcggtaat 540acgtaggtgg caagcgttat ccggaatcat
tgggcgtaaa gggtgcgtag gtggcacgat 600aagtctgaag taaaaggcaa
cagctcaact gttgtatgct ttggaaactg tcgagctaga 660gtgcagaaga
gggcgatgga attccatgtg tagcggtaaa atgcgtagat atatggagga
720acaccagtgg cgaaggcggt cgcctggtct gtaactgaca ctgatgcacg
aaagcgtggg 780gagcaaatag gattagatac cctagtagtc cacgccgtaa
acgatgagaa ctaagtgttg 840gagagattca gtgctgcagt taacgcaata
agttctccgc ctggggagta tgcacgcaag 900tgtgaaactc aaaggaattg
acgggggccc gcacaagcgg tggagtatgt ggtttaattc 960gaagcaacgc
gaagaacctt accaggcctt gacatggata taaatgttct agagatagaa
1020agatagctat atatcacaca ggtggtgcat ggttgtcgtc agctcgtgtc
gtgagatgtt 1080gggttaagtc ccgcaacgag cgcaaccctt gtcttctgtt
accagcatta agttggggac 1140tcaggagaga ctgccggtga caaaccggag
gaaggtgggg atgacgtcaa atcatcatgc 1200cccttatggc ctgggctaca
cacgtactac aatggcgcct acaaagagca gcgacaccgc 1260gaggtggagc
gaatctcata aagggcgtct cagttcggat tgaagtctgc aactcgactt
1320catgaagtcg gaatcgctag taatcgcaga tcagcatgct gcggtgaata
cgttctcggg 1380ccttgtacac accgcccgtc aaaccatggg agttggtaat
acccgaagcc ggtggcataa 1440ccgcaaggag tgagccgtcg aaggtaggac
cgatgactgg ggttaagtcg taacaaggta 1500tccctacggg aacgtgggga
tggatcacct ccttt 153581530DNABlautia sp. 8tcagagagtt tgatcctggc
tcaggatgaa cgctggcggc gtgcttaaca catgcaagtc 60gagcgaagca cttaagtgga
tctcttcgga ttgaaactta tttgactgag cggcggacgg 120gtgagtaacg
cgtgggtaac ctgcctcata cagggggata acagttagaa atggctgcta
180ataccgcata agcgcacagg accgcatggt ctggtgtgaa aaactccggt
ggtatgagat 240ggacccgcgt ctgattagct agttggaggg gtaacggccc
accaaggcga cgatcagtag 300ccggcctgag agggtgaacg gccacattgg
gactgagaca cggcccagac tcctacggga 360ggcagcagtg gggaatattg
cacaatgggg gaaaccctga tgcagcgacg ccgcgtgaag 420gaagaagtat
ctcggtatgt aaacttctat cagcagggaa gaaaatgacg gtacctgact
480aagaagcccc ggctaactac gtgccagcag ccgcggtaat acgtaggggg
caagcgttat 540ccggatttac tgggtgtaaa gggagcgtag acggaagagc
aagtctgatg tgaaaggctg 600gggcttaacc ccaggactgc attggaaact
gtttttctag agtgccggag aggtaagcgg 660aattcctagt gtagcggtga
aatgcgtaga tattaggagg aacaccagtg gcgaaggcgg 720cttactggac
ggtaactgac gttgaggctc gaaagcgtgg ggagcaaaca ggattagata
780ccctggtagt ccacgccgta aacgatgaat actaggtgtc gggtggcaaa
gccattcggt 840gccgcagcaa acgcaataag tattccacct ggggagtacg
ttcgcaagaa tgaaactcaa 900aggaattgac ggggacccgc acaagcggtg
gagcatgtgg tttaattcga agcaacgcga 960agaaccttac caagtcttga
catccctctg accggcccgt aacggggcct tcccttcggg 1020gcagaggaga
caggtggtgc atggttgtcg tcagctcgtg tcgtgagatg ttgggttaag
1080tcccgcaacg agcgcaaccc ctatccttag tagccagcag gtagagctgg
gcactctagg 1140gagactgccg gggataaccc ggaggaaggc ggggacgacg
tcaaatcatc atgcccctta 1200tgatttgggc tacacacgtg ctacaatggc
gtaaacaaag ggaagcgaga cagcgatgtt 1260gagcaaatcc caaaaataac
gtcccagttc ggactgcagt ctgcaactcg actgcacgaa 1320gctggaatcg
ctagtaatcg cgaatcagaa tgtcgcggtg aatacgttcc cgggtcttgt
1380acacaccgcc cgtcacacca tgggagtcag taacgcccga agtcagtgac
ccaaccttac 1440aggagggagc tgccgaaggc gggaccgata actggggtga
agtcgtaaca aggtagccgt 1500atcggaaggt gcggctggat cacctccttt
153091528DNABarnesiella intestinihominis 9cgaagagttt gatcctggct
caggatgaac gctagcgaca ggcctaacac atgcaagtcg 60aggggcagcg gagaggtagc
aatacctttg ccggcgaccg gcgcacgggt gagtaacacg 120tatgcaatcc
acctgtaaca gggggataac ccggagaaat ccggactaat accccataat
180atgggcgctc cgcatggaga gtccattaaa gagagcaatt ttggttacag
acgagcatgc 240gctccattag ccagttggcg gggtaacggc ccaccaaagc
gacgatggat aggggttctg 300agaggaaggt cccccacatt ggaactgaga
cacggtccaa actcctacgg gaggcagcag 360tgaggaatat tggtcaatgg
tcggcagact gaaccagcca agtcgcgtga gggaagacgg 420ccctacgggt
tgtaaacctc ttttgtcgga gagtaaagta cgctacgtgt agtgtattgc
480aagtatccga agaaaaagca tcggctaact ccgtgccagc agccgcggta
atacggagga 540tgcgagcgtt atccggattt attgggttta aagggtgcgt
aggcggcacg ccaagtcagc 600ggtgaaattt ccgggctcaa cccggactgt
gccgttgaaa ctggcgagct agagtgcaca 660agaggcaggc ggaatgcgtg
gtgtagcggt gaaatgcata gatatcacgc agaaccccga 720ttgcgaaggc
agcctgctag ggtgcgacag acgctgaggc acgaaagcgt gggtatcgaa
780caggattaga taccctggta gtccacgcag taaacgatga atactaactg
tttgcgatac 840aatgtaagcg gtacagcgaa agcgttaagt attccacctg
gggagtacgc cggcaacggt 900gaaactcaaa ggaattgacg ggggcccgca
caagcggagg aacatgtggt ttaattcgat 960gatacgcgag gaaccttacc
cgggctcaaa cgcaggggga atgccggtga aagtcggcag 1020ctagcaatag
tcacctgcga ggtgctgcat ggttgtcgtc agctcgtgcc gtgaggtgtc
1080ggcttaagtg ccataacgag cgcaacccct atggacagtt actaacgggt
gaagccgagg 1140actctgtcta gactgccggc gcaagccgcg aggaaggtgg
ggatgacgtc aaatcagcac 1200ggcccttacg tccggggcga cacacgtgtt
acaatggcag gtacagaagg cagccagtca 1260gcaatgacgc gcgaatcccg
aaaacctgtc tcagttcgga ttggagtctg caacccgact 1320ccatgaagct
ggattcgcta gtaatcgcgc atcagccatg gcgcggtgaa tacgttcccg
1380ggccttgtac acaccgcccg tcaagccatg gaagccggga gtacctgaag
catgcaaccg 1440caaggagcgt acgaaggtaa taccggtaac tggggctaag
tcgtaacaag gtagccgtac 1500cggaaggtgc ggctggaaca cctccttt
1528101525DNAAlistipes timonensis 10atggagagtt tgatcctggc
tcaggatgaa cgctagcggc aggcctaaca catgcaagtc 60gaggggcagc gggattgaag
cttgcttcaa tcgccggcga ccggcgcacg ggtgcgtaac 120gcgtatgcaa
cctacccaga acagggggat aacactgaga aattggtact aatatcccat
180aacatcataa ggggcatccc ttttggttga aaactccggt ggttctggat
gggcatgcgt 240tgtattagct agttggtgag gtaacggctc accaaggcaa
cgatacatag ggggactgag 300aggttaaccc cccacattgg tactgagaca
cggaccaaac tcctacggga ggcagcagtg 360aggaatattg gtcaatggac
gcaagtctga accagccatg ccgcgtgcag gaagacggct 420ctatgagttg
taaactgctt ttgtactagg gtaaactcag atacgtgtat ctgactgaaa
480gtatagtacg aataaggatc ggctaactcc gtgccagcag ccgcggtaat
acggaggatt 540caagcgttat ccggatttat tgggtttaaa gggtgcgtag
gcggtttgat aagttagagg 600tgaaataccg gtgcttaaca ccggaactgc
ctctaatact gttgagctag agagtagttg 660cggtaggcgg aatgtatggt
gtagcggtga aatgcttaga gatcatacag
aacaccgatt 720gcgaaggcag cttaccaaac tatatctgac gttgaggcac
gaaagcgtgg ggagcaaaca 780ggattagata ccctggtagt ccacgcagta
aacgatgata actcgctgtc ggcgatacac 840agtcggtggc taagcgaaag
cgataagtta tccacctggg gagtacgttc gcaagaatga 900aactcaaagg
aattgacggg ggcccgcaca agcggaggaa catgtggttt aattcgatga
960tacgcgagga accttacccg ggcttgaaag ttagtgacgg atctggaaac
aggtcttccc 1020ttcggggcgc gaaactaggt gctgcatggt tgtcgtcagc
tcgtgccgtg aggtgtcggg 1080ttaagtccca taacgagcgc aacccctacc
gttagttgcc atcaggtcaa gctgggcact 1140ctgacgggac tgccggtgta
agccgagagg aaggtgggga tgacgtcaaa tcagcacggc 1200ccttacgtcc
ggggccacac acgtgttaca atggtaggta cagagggcag ctacccagcg
1260atgggatgcg aatctcgaaa gcctatctca gttcggatcg gaggctgaaa
cccgcctccg 1320tgaagttgga ttcgctagta atcgcgcatc agccatggcg
cggtgaatac gttcccgggc 1380cttgtacaca ccgcccgtca agccatggaa
gctgggggtg cctgaagttc gtgaccgcaa 1440ggagcgacct agggcaaaac
cggtgactgg ggctaagtcg taacaaggta gccgtaccgg 1500aaggtgcggc
tggaacacct ccttt 1525111528DNABlautia sp. 11tcagagagtt tgatcctggc
tcaggatgaa cgctggcggc gtgcttaaca catgcaagtc 60gagcgaagca cttgccattg
actcttcgga agatttggca tttgactgag cggcggacgg 120gtgagtaacg
cgtgggtaac ctgcctcata caggggaata acagttagaa atggctgcta
180atgccgcata agcgcacagg accgcatggt ctggtgtgaa aaactgaggt
ggtatgagat 240gggcccgcgt ctgattaggt agttggcggg gtaacggccc
accaagccga cgatcagtag 300ccgacctgag agggtgaccg gccacattgg
gactgagaca cggcccagac tcctacggga 360ggcagcagtg gggaatattg
cacaatggag gaaactctga tgcagcgacg ccgcgtgaag 420gaagaagtat
ctcggtatgt aaacttctat cagcagggaa gaaaatgacg gtacctgact
480aagaagcccc ggctaactac gtgccagcag ccgcggtaat acgtaggggg
caagcgttat 540ccggatttac tgggtgtaaa gggagcgtag acggacgggc
aagtctgatg tgaaagcccg 600gggcttaacc ccgggactgc attggaaact
gtccatcttg agtgccggag aggtaagcgg 660aattcctagt gtagcggtga
aatgcgtaga tattaggagg aacaccagtg gcgaaggcgg 720cttactggac
ggtaactgac gttgaggctc gaaagcgtgg ggagcaaaca ggattagata
780ccctggtagt ccacgccgta aacgatgaat actaggtgtc gggttgcaaa
gcaatccggt 840gccgcagcaa acgcagtaag tattccacct ggggagtacg
ttcgcaagaa tgaaactcaa 900aggaattgac ggggacccgc acaagcggtg
gagcatgtgg tttaattcga agcaacgcga 960agaaccttac caagtcttga
catctgcctg accgttcctt aaccggaact ttccttcggg 1020acaggcaaga
caggtggtgc atggttgtcg tcagctcgtg tcgtgagatg ttgggttaag
1080tcccgcaacg agcgcaaccc ctgtccttag tagccagcag tccggctggg
cactctaggg 1140agactgccgg ggataacccg gaggaaggcg gggacgacgt
caaatcatca tgccccttat 1200gatttgggct acacacgtgc tacaatggcg
taaacaaagg gaagcggagt ggtgacactg 1260agcaaatctc aaaaataacg
tcccagttcg gactgcagtc tgcaactcga ctgcacgaag 1320ctggaatcgc
tagtaatcgc gaatcagaat gtcgcggtga atacgttccc gggtcttgta
1380cacaccgccc gtcacaccat gggagtcagt aacgcccgaa gtcagtgacc
taaccgcaag 1440ggaggagctg ccgaaggcgg gaccgataac tggggtgaag
tcgtaacaag gtagccgtat 1500cggaaggtgc ggctggatca cctccttt
1528121530DNALachnospira sp. 12ttatgagagt ttgatcctgg ctcaggatga
acgctggcgg cgtgcttaac acatgcaagt 60cgaacgaagc atttaagacg gattctttcg
ggatgaagac ttttatgact gagtggcgga 120cgggtgagta acgcgtgggt
aacctgcctc acacaggggg atagcagttg gaaacggctg 180ataataccgc
ataagcgcac agtaccgcat ggtacagtgt gaaaaactcc ggtggtgtga
240gatggacccg cgtctgatta gcttgttggc agggtaacgg cctaccaagg
caacgatcag 300tagccgacct gagagggtga ccggccacat tgggactgag
acacggccca gactcctacg 360ggaggcagca gtggggaata ttgcacaatg
gaggaaactc tgatgcagcg acgccgcgtg 420agtgaagaag taattcgtta
tgtaaagctc tatcagcagg gaagatagtg acggtacctg 480actaagaagc
tccggctaaa tacgtgccag cagccgcggt aatacgtatg gagcaagcgt
540tatccggatt tactgggtgt aaagggagtg taggtggcat cacaagtcag
aagtgaaagc 600ccggggctca accccgggac tgcttttgaa actgtggagc
tggagtgcag gagaggcaag 660tggaattcct agtgtagcgg tgaaatgcgt
agatattagg aggaacacca gtggcgaagg 720cggcttgctg gactgtaact
gacactgagg ctcgaaagcg tggggagcaa acaggattag 780ataccctggt
agtccacgcc gtaaacgatg aatactaggt gtcggggctc ataagagctt
840cggtgccgca gcaaacgcaa taagtattcc acctggggag tacgttcgca
agaatgaaac 900tcaaaggaat tgacggggac ccgcacaagc ggtggagcat
gtggtttaat tcgaagcaac 960gcgaagaacc ttaccaagtc ttgacatcct
cttgaccggt cagtaatgtg accttttctt 1020cggaacaaga gtgacaggtg
gtgcatggtt gtcgtcagct cgtgtcgtga gatgttgggt 1080taagtcccgc
aacgagcgca acccctattc ttagtagcca gcatttaagg tgggcactct
1140aggaagactg ccagggataa cctggaggaa ggtggggatg acgtcaaatc
atcatgcccc 1200ttatgacttg ggctacacac gtgctacaat ggcgtaaaca
aagtgaagcg agagtgtgag 1260cttaagcaaa tcacaaaaat aacgtctcag
ttcggattgt agtctgcaac tcgactacat 1320gaagctggaa tcgctagtaa
tcgcgaatca gaatgtcgcg gtgaatacgt tcccgggtct 1380tgtacacacc
gcccgtcaca ccatgggagt cggaaatgcc cgaagtcggt gacctaacga
1440aagaaggagc cgccgaaggc aggtctgata actggggtga agtcgtaaca
aggtagccgt 1500atcggaaggt gcggctggat cacctccttt
1530131507DNARuminococcus callidus 13taaagagttt gatcctggct
caggacgaac gctggcggca cgcttaacac atgcaagtcg 60aacggagaat atcgaagctt
gctttgatat tcttagtggc ggacgggtga gtaacacgtg 120agtaacctgc
ctctgagagt gggatagctt ctggaaacgg atggtaatac cgcatgaaat
180catagtatcg catggtacaa tgatcaaaga tttatcgctc agagatggac
tcgcgtctga 240ttagctagtt ggtaaggtaa cggcttacca aggcgacgat
cagtagccgg actgagaggt 300tgatcggcca cattgggact gagacacggc
ccagactcct acgggaggca gcagtgggga 360atattgcaca atgggggaaa
ccctgatgca gcgatgccgc gtggaggaag aaggttttcg 420gattgtaaac
tcctgttgaa gaggacgata atgacggtac tcttttagaa agctccggct
480aactacgtgc cagcagccgc ggtaatacgt agggagcgag cgttgtccgg
aattactggg 540tgtaaaggga gcgtaggcgg gacggcaagt cagatgtgaa
aactatgggc tcaacccata 600gactgcattt gaaactgttg ttcttgagtg
aggtagaggt aagcggaatt cctggtgtag 660cggtgaaatg cgtagagatc
aggaggaaca tcggtggcga aggcggctta ctgggccttt 720actgacgctg
aggctcgaaa gcgtggggag caaacaggat tagataccct ggtagtccac
780gccgtaaacg atgattacta ggtgtggggg gactgacccc ttccgtgccg
cagttaacac 840aataagtaat ccacctgggg agtacggccg caaggttgaa
actcaaagga attgacgggg 900gcccgcacaa gcagtggagt atgtggttta
attcgaagca acgcgaagaa ccttaccagg 960tcttgacatc gagtgacgta
cctagagata ggtattttct tcggaacaca aagacaggtg 1020gtgcatggtt
gtcgtcagct cgtgtcgtga gatgttgggt taagtcccgc aacgagcgca
1080acccttacca ttagttgcta cgcaagagca ctctaatggg actgccgttg
acaaaacgga 1140ggaaggtggg gatgacgtca aatcatcatg ccccttatga
cctgggctac acacgtacta 1200caatggcaat ataacagagg gaagcaatac
agcgatgtgg agcaaatccc caaaaattgt 1260cccagttcag attgcaggct
gcaactcgcc tgcatgaagt cggaattgct agtaatcgca 1320gatcagcatg
ctgcggtgaa tacgttcccg ggccttgtac acaccgcccg tcacaccatg
1380ggagtcggta acacccaaag ccggtcgtct aaccttcggg aggacgccgt
ctaaggtggg 1440attgatgact ggggtgaagt cgtaacaagg tagccgtatc
ggaaggtgcg gctggatcac 1500ctccttt 1507141530DNARoseburia faecis
14atgagagttt gatcctggct caggatgaac gctggcggcg tgcttaacac atgcaagtcg
60aacgaagcac tctatttgat tttcttcgga aatgaagatt ttgtgactga gtggcggacg
120ggtgagtaac gcgtgggtaa cctgcctcat acagggggat aacagttgga
aacgactgct 180aataccgcat aagcgcacag gatcgcatgg tccggtgtga
aaaactccgg tggtatgaga 240tggacccgcg tctgattagc cagttggcag
ggtaacggcc taccaaagcg acgatcagta 300gccgacctga gagggtgacc
ggccacattg ggactgagac acggcccaaa ctcctacggg 360aggcagcagt
ggggaatatt gcacaatggg ggaaaccctg atgcagcgac gccgcgtgag
420cgaagaagta tttcggtatg taaagctcta tcagcaggga agaagaatga
cggtacctga 480ctaagaagca ccggctaaat acgtgccagc agccgcggta
atacgtatgg tgcaagcgtt 540atccggattt actgggtgta aagggagcgc
aggcggtgcg gcaagtctga tgtgaaagcc 600cggggctcaa ccccggtact
gcattggaaa ctgtcgtact agagtgtcgg aggggtaagt 660ggaattccta
gtgtagcggt gaaatgcgta gatattagga ggaacaccag tggcgaaggc
720ggcttactgg acgataactg acgctgaggc tcgaaagcgt ggggagcaaa
caggattaga 780taccctggta gtccacgccg taaacgatga atactaggtg
tcggggagca ttgctcttcg 840gtgccgcagc aaacgcaata agtattccac
ctggggagta cgttcgcaag aatgaaactc 900aaaggaattg acggggaccc
gcacaagcgg tggagcatgt ggtttaattc gaagcaacgc 960gaagaacctt
accaagtctt gacatcccga tgacagagta tgtaatgtac tttctcttcg
1020gagcatcggt gacaggtggt gcatggttgt cgtcagctcg tgtcgtgaga
tgttgggtta 1080agtcccgcaa cgagcgcaac ccctgttctt agtagccagc
ggttcggccg ggcactctag 1140ggagactgcc agggataacc tggaggaagg
cggggatgac gtcaaatcat catgcccctt 1200atgacttggg ctacacacgt
gctacaatgg cgtaaacaaa gggaagcgga gccgtgaggc 1260cgagcaaatc
tcaaaaataa cgtctcagtt cggactgtag tctgcaaccc gactacacga
1320agctggaatc gctagtaatc gcagatcaga atgctgcggt gaatacgttc
ccgggtcttg 1380tacacaccgc ccgtcacacc atgggagttg gaaatgcccg
aagtcagtga cccaaccgca 1440aggagggagc tgccgaaggc aggttcgata
actggggtga agtcgtaaca aggtagccgt 1500atcggaaggt gcggctggat
cacctccttt 1530151473DNAFaecalibacterium prausnitzii 15agagtttgat
cctggctcag gacgaacgct ggcggcgcgc ctaacacatg caagtcgaac 60gagagagagg
gagcttgctt ccttgatcga gtggcgaacg ggtgagtaac gcgtgaggaa
120cctgcctcaa agagggggac aacagttgga aacgactgct aataccgcat
aagcccacga 180cccggcatcg ggaagaggga aaaggagcaa tccgctttga
gatggcctcg cgtccgatta 240gctagttggt gaggtaacgg cccaccaagc
gacgatcggt agccggactg agaggttgaa 300cggccacatt gggactgaga
cacggcccag actcctacgg gaggcagcag tggggaatat 360tgcacaatgg
gggaaaccct gatgcagcga cgccgcgtgg aggaagaagg tcttcggatt
420gtaaactcct gttgttgagg aagataatga cggtactcaa caaggaagtg
acggctaact 480acgtgccagc agccgcggta aaacgtaggt cacaagcgtt
gtccggaatt actgggtgta 540aagggagcgc aggcgggcga tcaagttgga
agtgaaatcc atgggctcaa cccatgaact 600gctttcaaaa ctggtcgtct
tgagtagtgc agaggtaggc ggaattcccg gtgtagcggt 660ggaatgcgta
gatatcggga ggaacaccag tggcgaaggc ggcctactgg gcaccaactg
720acgctgaggc tcgaaagtgt gggtagcaaa caggattaga taccctggta
gtccacaccg 780taaacgatga ttactaggtg ttgggagatt gaccctctca
gtgccgcagt taacacaata 840agtaatccac ctggggagta cgaccgcaag
gttgaaactc aaaggaattg acgggggccc 900gcacaagcag tggagtatgt
ggtttaattc gacgcaacgc gaagaacctt accaagtctt 960gacatccctt
gacgatgctg gaaacagtat ttctcttcgg agcaaggaga caggtggtgc
1020atggttgtcg tcagctcgtg tcgtgagatg ttgggttaag tcccgcaacg
agcgcaaccc 1080ttatggtcag ttactacgca agaggactct ggccagactg
ccgttgacaa aacggaggaa 1140ggtggggatg acgtcaaatc atcatgccct
ttatgacttg ggctacacac gtactacaat 1200ggcgttaaac aaagagaagc
aagaccgcga ggtggagcaa aactcagaaa caacgtccca 1260gttcggactg
caggctgcaa ctcgcctgca cgaagtcgga attgctagta atcgtggatc
1320agcatgccac ggtgaatacg ttcccgggcc ttgtacacac cgcccgtcac
accatgagag 1380ccggggggac ccgaagtcgg tagtctaacc gcaaggagga
cgccgccgaa ggtaaaactg 1440gtgattgggg tgaagtcgta acaaggtagc cgt
1473161539DNAAlistipes obesi 16atggagagtt tgatcctggc tcaggatgaa
cgctagcggc aggcttaaca catgcaagtc 60gaggggcagc ataatggtag taatactatt
gatggcgacc ggcggacggg tgcgtaacgc 120gtatgcaacc taccctttac
agggggataa cactgagaaa tcggtactaa taccccataa 180tattctggga
ggcatctttc ggagttgaaa gctttggtgg taaaggatgg gcatgcgttg
240tattagctag ttggtaaggt aacggcttac caaggcgacg atacataggg
ggactgagag 300gttaaccccc cacattggta ctgagacacg gaccaaactc
ctacgggagg cagcagtgag 360gaatattggt caatggacgg aagtctgaac
cagccatgcc gcgtgcagga agacggctct 420atgagttgta aactgctttt
gtacgagggt aaacgcagat acgtgtatct gcctgaaagt 480atcgtacgaa
taaggatcgg ctaactccgt gccagcagcc gcggtaatac ggaggatcca
540agcgttatcc ggatttattg ggtttaaagg gtgcgtaggc ggtttagtaa
gtcagcggtg 600aaattttggt gcttaacacc aaacgtgccg ttgatactgc
tgggctagag agtagttgcg 660gtaggcggaa tgtatggtgt agcggtgaaa
tgcttagaga tcatacagaa caccgattgc 720gaaggcagct taccaaacta
tatctgacgt tgaggcacga aagcgtgggg agcaaacagg 780attagatacc
ctggtagtcc acgcagtaaa cgatgatagc tcgttgtcgg cgatacacag
840tcggtgacta agagaaatcg ataagctatc cacctgggga gtacgttcgc
aagaatgaaa 900ctcaaaggaa ttgacggggg cccgcacaag cggaggaaca
tgtggtttaa ttcgatgata 960cgcgaggaac cttacccggg cttgaaagtt
actgacgatt ctggaaacag gatttccctt 1020cggggcagga aactaggtgc
tgcatggttg tcgtcagctc gtgccgtgag gtgtcgggtt 1080aagtcccata
acgagcgcaa cccctactga tagttgccat cagagcgttt gagcgatcaa
1140acaagctggg cactctatcg ggactgccgg tgtaagccga gaggaaggtg
gggatgacgt 1200caaatcagca cggcccttac gtccggggcg acacacgtgt
tacaatggta ggtacagagg 1260gcagccaccc agtgatgggg agcgaatctc
gaaagcctat ctcagttcgg attggaggct 1320gaaactcgcc tccatgaagt
tggattcgct agtaatcgcg catcagccat ggcgcggtga 1380atacgttccc
gggccttgta cacaccgccc gtcaagccat gggagttggg ggtgcctgaa
1440gttcgtgacc gaaaggagcg acctagggca aaaccgatga ctggggctaa
gtcgtaacaa 1500ggtagccgta ccggaaggtg cggctggaac acctccttt
1539171525DNAButyricicoccus sp. 17tttagagagt ttgatcctgg ctcaggatga
acgctggcgg cgtgcctaac acatgcaagt 60cgaacggagt tattttggaa atctcttcgg
agatggaatt cataacttag tggcggacgg 120gtgagtaacg cgtgagcaat
ctgcccttag gtgggggata acagccggaa acggctgcta 180ataccgcata
acacattgaa gccgcatggt tttgatgtca aagatttatt gcctttggat
240gagctcgcgt ctgattagct ggttggcggg gtaacggccc accaaggcga
cgatcagtag 300ccggactgag aggttgaacg gccacattgg gactgagaca
cggcccagac tcctacggga 360ggcagcagtg gggaatattg cgcaatgggg
gaaaccctga cgcagcaacg ccgcgtgatt 420gaagaaggcc ttcgggttgt
aaagatcttt aattggggac gaaaaatgac ggtacccaaa 480gaataagctc
cggctaacta cgtgccagca gccgcggtaa tacgtaggga gcaagcgtta
540tccggattta ctgggtgtaa agggcgagta ggcgggctgg caagttggga
gtgaaatccc 600ggggcttaac cccggaactg ctttcaaaac tgctggtctt
gagtgatgga gaggcaggcg 660gaattccgtg tgtagcggtg aaatgcgtag
atatacggag gaacaccagt ggcgaaggcg 720gcctgctgga cattaactga
cgctgaggag cgaaagcgtg gggagcaaac aggattagat 780accctggtag
tccacgccgt aaacgatgga tactaggtgt gggaggtatt gaccccttcc
840gtgccggagt taacacaata agtatcccac ctggggagta cggccgcaag
gttgaaactc 900aaaggaattg acgggggccc gcacaagcag tggagtatgt
ggtttaattc gaagcaacgc 960gaagaacctt accaggtctt gacatccctc
tgaccgccct agagataggg tttcccttcg 1020gggcagaggt gacaggtggt
gcatggttgt cgtcagctcg tgtcgtgaga tgttgggtta 1080agtcccgcaa
cgagcgcaac ccttacggtt agttgatacg caagatcact ctagccggac
1140tgccgttgac aaaacggagg aaggtgggga cgacgtcaaa tcatcatgcc
ccttatgacc 1200tgggctacac acgtactaca atggcagtca tacagaggga
agcaaaacag tgatgtggag 1260caaatcccta aaagctgtcc cagttcagat
tgcaggctgc aactcgcctg catgaagtcg 1320gaattgctag taatcgcgga
tcagcatgcc gcggtgaata cgttcccggg ccttgtacac 1380accgcccgtc
acaccatgag agccggtaat acccgaagtc cgtagcctaa ccgcaaggag
1440ggcgcggccg aaggtaggac tggtaattag ggtgaagtcg taacaaggta
gccgtatcgg 1500aaggtgcggc tggatcacct ccttt
1525181506DNAGordonibacter urolithinfaciens 18acggagagtt tgatcctggc
tcaggatgaa cgctggcggc gtgcctaaca catgcaagtc 60gaacggttaa ggcgccttcg
ggcgcgaata gagtggcgaa cgggtgagta acacgtgacc 120aacctgcccc
cctccccggg ataacgcgag gaaacccgcg ctaataccgg atactccgcc
180cctcccgcat gggaggggcg ggaaagcccc gacggagggg gatggggtcg
cggcccatta 240ggtagacggc gaggcaacgg cccaccgtgc ctgcgatggg
tagccgggtt gagagaccga 300ccggccacat tgggactgag atacggccca
gactcctacg ggaggcagca gtggggaatt 360ttgcgcaatg gggggaaccc
tgacgcagca acgccgcgtg cgggacgaag gccttcgggt 420tgtaaaccgc
tttcagcagg gaagaagttg acggtacctg cagaagaagc cccggctaac
480tacgtgccag cagccgcggt aatacgtagg gggcgagcgt tatccggatt
cattgggcgt 540aaagcgcgcg taggcggccc gtcaagcgga acctctaacc
cgagggctca acccccggcc 600gggttccgaa ctggcaggct cgagtttggt
agaggaagat ggaattcccg gtgtagcggt 660ggaatgcgca gatatcggga
agaacaccga tggcgaaggc agtcttctgg gccatcaact 720gacgctgagg
cgcgaaagct gggggagcga acaggattag ataccctggt agtcccagcc
780gtaaacgatg ggtgctaggt gtggggggat catccctccg tgccgcagcc
aacgcattaa 840gcaccccgcc tggggagtac ggccgcaagg ctaaaactca
aaggaattga cgggggcccg 900cacaagcagc ggagcatgtg gcttaattcg
aagcaacgcg aagaacctta ccagggcttg 960acatgctggt gaagccgggg
aaacccggtg gccgagagga gccagcgcag gtggtgcatg 1020gctgtcgtca
gctcgtgtcg tgagatgttg ggttaagtcc cgcaacgagc gcaacccctg
1080ccatatgttg ccagcattca gttggggact catatgggac tgccggcgtc
aagccggagg 1140aaggtgggga cgacgtcaag tcatcatgcc ctttatgccc
tgggctgcac acgtgctaca 1200atggccggta caacgggccg cgacctggcg
acaggaagcg aatccctcaa agccggcccc 1260agttcggatc ggaggctgca
acccgcctcc gtgaagtcgg agttgctagt aatcgcggat 1320cagcatgccg
cggtgaatac gttcccgggc cttgtacaca ccgcccgtca caccacccga
1380gtcgtctgca cccgaagccg ccggccgaac ccgcaagggg cggaggcgtc
gaaggtgtgg 1440agggtaaggg gggtgaagtc gtaacaaggt agccgtaccg
gaaggtgcgg ctggatcacc 1500tccttt 1506191528DNABlautia sp.
19tcagagagtt tgatcctggc tcaggatgaa cgctggcggc gtgcttaaca catgcaagtc
60gagcgaagca cttgccattg actcttcgga agatttggca tttgactgag cggcggacgg
120gtgagtaacg cgtgggtaac ctgcctcata caggggaata acagttagaa
atggctgcta 180atgccgcata agcgcacagg accgcatggt ctggtgtgaa
aaactgaggt ggtatgagat 240gggcccgcgt ctgattaggt agttggcggg
gtaacggccc accaagccga cgatcagtag 300ccgacctgag agggtgaccg
gccacattgg gactgagaca cggcccagac tcctacggga 360ggcagcagtg
gggaatattg cacaatggag gaaactctga tgcagcgacg ccgcgtgaag
420gaagaagtat ctcggtatgt aaacttctat cagcagggaa gaaaatgacg
gtacctgact 480aagaagcccc ggctaactac gtgccagcag ccgcggtaat
acgtaggggg caagcgttat 540ccggatttac tgggtgtaaa gggagcgtag
acggacgggc aagtctgatg tgaaagcccg 600gggcttaacc ccgggactgc
attggaaact gtccatcttg agtgccggag aggtaagcgg 660aattcctagt
gtagcggtga aatgcgtaga tattaggagg aacaccagtg gcgaaggcgg
720cttactggac ggtaactgac gttgaggctc gaaagcgtgg ggagcaaaca
ggattagata 780ccctggtagt ccacgccgta aacgatgaat actaggtgtc
gggttgcaaa gcaatccggt 840gccgcagcaa acgcagtaag tattccacct
ggggagtacg ttcgcaagaa tgaaactcaa 900aggaattgac ggggacccgc
acaagcggtg gagcatgtgg tttaattcga agcaacgcga 960agaaccttac
caagtcttga catctgcctg accgttcctt aaccggaact ttccttcggg
1020acaggcaaga caggtggtgc atggttgtcg tcagctcgtg tcgtgagatg
ttgggttaag 1080tcccgcaacg agcgcaaccc ctgtccttag tagccagcag
tccggctggg cactctaggg 1140agactgccgg ggataacccg gaggaaggcg
gggacgacgt caaatcatca tgccccttat 1200gatttgggct acacacgtgc
tacaatggcg taaacaaagg gaagcggagt ggtgacactg 1260agcaaatctc
aaaaataacg tcccagttcg gactgcagtc tgcaactcga ctgcacgaag
1320ctggaatcgc tagtaatcgc gaatcagaat gtcgcggtga atacgttccc
gggtcttgta 1380cacaccgccc gtcacaccat gggagtcagt aacgcccgaa
gtcagtgacc taaccgcaag 1440ggaggagctg ccgaaggcgg gaccgataac
tggggtgaag tcgtaacaag gtagccgtat 1500cggaaggtgc ggctggatca
cctccttt
1528201530DNALachnospira sp. 20ttatgagagt ttgatcctgg ctcaggatga
acgctggcgg cgtgcttaac acatgcaagt 60cgaacgaagc atttaagacg gattctttcg
ggatgaagac ttttatgact gagtggcgga 120cgggtgagta acgcgtgggt
aacctgcctc acacaggggg atagcagttg gaaacggctg 180ataataccgc
ataagcgcac agtaccgcat ggtacagtgt gaaaaactcc ggtggtgtga
240gatggacccg cgtctgatta gcttgttggc agggtaacgg cctaccaagg
caacgatcag 300tagccgacct gagagggtga ccggccacat tgggactgag
acacggccca gactcctacg 360ggaggcagca gtggggaata ttgcacaatg
gaggaaactc tgatgcagcg acgccgcgtg 420agtgaagaag taattcgtta
tgtaaagctc tatcagcagg gaagatagtg acggtacctg 480actaagaagc
tccggctaaa tacgtgccag cagccgcggt aatacgtatg gagcaagcgt
540tatccggatt tactgggtgt aaagggagtg taggtggcat cacaagtcag
aagtgaaagc 600ccggggctca accccgggac tgcttttgaa actgtggagc
tggagtgcag gagaggcaag 660tggaattcct agtgtagcgg tgaaatgcgt
agatattagg aggaacacca gtggcgaagg 720cggcttgctg gactgtaact
gacactgagg ctcgaaagcg tggggagcaa acaggattag 780ataccctggt
agtccacgcc gtaaacgatg aatactaggt gtcggggctc ataagagctt
840cggtgccgca gcaaacgcaa taagtattcc acctggggag tacgttcgca
agaatgaaac 900tcaaaggaat tgacggggac ccgcacaagc ggtggagcat
gtggtttaat tcgaagcaac 960gcgaagaacc ttaccaagtc ttgacatcct
cttgcccggt cagtaatgtg accttttctt 1020cggaacaaga gtgacaggtg
gtgcatggtt gtcgtcagct cgtgtcgtga gatgttgggt 1080taagtcccgc
aacgagcgca acccctattc ttagtagcca gcatataagg tgggcactct
1140aggaagactg ccagggataa cctggaggaa ggtggggatg acgtcaaatc
atcatgcccc 1200ttatgacttg ggctacacac gtgctacaat ggcgtaaaca
aagtgaagcg agagtgtgag 1260cttaagcaaa tcacaaaaat aacgtctcag
ttcggattgt agtctgcaac tcgactacat 1320gaagctggaa tcgctagtaa
tcgcgaatca gaatgtcgcg gtgaatacgt tcccgggtct 1380tgtacacacc
gcccgtcaca ccatgggagt cggaaatgcc cgaagtcggt gacctaacga
1440aagaaggagc cgccgaaggc aggtctgata actggggtga agtcgtaaca
aggtagccgt 1500atcggaaggt gcggctggat cacctccttt
1530211527DNAEisenbergiella sp.misc_featureR=A or G, Y=C or T
21agagagtttg atcctggctc aggatgaacg ctggcggcgt gcctaacaca tgcaagtcga
60acggagttat gcagaggaag ttttcggatg gaatcggcgt aacttagtgg cggacgggtg
120agtaacgcgt gggaaacctg ccctgtaccg ggggataaca cttagaaata
ggtgctaata 180ccgcataagc gcacagcttc acatgargca gtgtgaaaaa
ctccggtggt acaggatggt 240cccgcgtctg attagccagt tggcagggta
ayggcctacc aaagcgacga tcagtagccg 300gcctgagagg gtgaacggcc
acattgggac tgagacacgg cccaaactcc tacgggaggc 360agcagtgggg
aatattgcac aatgggggaa accctgatgc agcgacgccg cgtgagtgaa
420gaagtatttc ggtatgtaaa gctctatcag cagggaagaa aatgacggta
cctgactaag 480aagccccggc taactacgtg ccagcagccg cggtaatacg
tagggggcaa gcgttatccg 540gatttactgg gtgtaaaggg agcgtagacg
gcatgacaag ccagatgtga aaacccaggg 600ctcaaccctg ggactgcatt
tggaactgcc aggctggagt gcaggagagg taagcggaat 660tcctagtgta
gcggtgaaat gcgtagatat taggaggaac accagtggcg aaggcggctt
720actggactgt aactgacgtt gaggctcgaa agcgtgggga gcaaacagga
ttagataccc 780tggtagtcca cgcggtaaac gatgattgct aggtgtaggt
gggtatggac ccatcggtgc 840cgcagctaac gcaataagca atccacctgg
ggagtacgtt cgcaagaatg aaactcaaag 900gaattgacgg ggacccgcac
aagcggtgga gcatgtggtt taattcgaag caacgcgaag 960aaccttacca
agtcttgaca tcccaatgac gtgtccgtaa cggggcattc tcttcggagc
1020attggagaca ggtggtgcat ggttgtcgtc agctcgtgtc gtgagatgtt
gggttaagtc 1080ccgcaacgag cgcaaccctt atccttagta gccagcaggt
aragctgggc actctaggga 1140gactgccggg gataacccgg aggaaggcgg
ggaygacgtc aaatcatcat gccccttatg 1200atttgggcta cacacgtgct
acaatggcgt aaacaaaggg aagcgagaca gtgatgttga 1260gcaaatccca
gaaataacgt ctcagttcgg attgtagtct gcaactcgac tacatgaagc
1320tggaatcgct agtaatcgcg aatcagcatg tcgcggtgaa tacgttcccg
ggtcttgtac 1380acaccgcccg tcacaccatg ggagttggaa atgcccgaag
cctgtgacct aaccgcaagg 1440gaggagcagt cgaaggcagg tctaataact
ggggtgaagt cgtaacaagg tagccgtatc 1500ggaaggtgcg gctggatcac ctccttt
1527221525DNAButyricicoccus sp.misc_featureW=A or T 22tttagagagt
ttgatcctgg ctcaggatga acgctggcgg cgtgcctaac acatgcaagt 60cgaacggagt
tattttggaa atctcttcgg ggatggaatt cataacttag tggcggacgg
120gtgagtaacg cgtgagcaat ctgcccttag gtgggggata acagccggaa
acggctgcta 180ataccgcata acacattgaa gccgcatggt tttgatgtca
aagatttatt gcctttggat 240gagctcgcgt ctgattagct ggttggcggg
gtaacggccc accaaggcga cgatcagtag 300ccggactgag aggttgaacg
gccacattgg gactgagaca cggcccagac tcctacggga 360ggcagcagtg
gggaatattg cgcaatgggg gaaaccctga cgcagcaacg ccgcgtgatt
420gaagaaggcc ttcgggttgt aaagatcttt aattggggac gaawwwtgac
ggtacccaaa 480gaataagctc cggctaacta cgtgccagca gccgcggtaa
tacgtaggga gcaagcgtta 540tccggattta ctgggtgtaa agggcgagta
ggcgggctgg caagttggga gtgaaatccc 600ggggcttaac cccggaactg
ctttcaaaac tgctggtctt gagtgatgga gaggcaggcg 660gaattccgtg
tgtagcggtg aaatgcgtag atatacggag gaacaccagt ggcgaaggcg
720gcctgctgga cattaactga cgctgaggag cgaaagcgtg gggagcaaac
aggattagat 780accctggtag tccacgccgt aaacgatgga tactaggtgt
gggaggtatt gaccccttcc 840gtgccggagt taacacaata agtatcccac
ctggggagta cggccgcaag gttgaaactc 900aaaggaattg acgggggccc
gcacaagcag tggagtatgt ggtttaattc gaagcaacgc 960gaagaacctt
accaggtctt gacatccctc tgaccgccct agagataggg tttcccttcg
1020gggcagaggt gacaggtggt gcatggttgt cgtcagctcg tgtcgtgaga
tgttgggtta 1080agtcccgcaa cgagcgcaac ccttacggtt agttgatacg
aaagatcact ctagccggac 1140tgccgttgac aaaacggagg aaggtgggga
cgacgtcaaa tcatcatgcc ccttatgacc 1200tgggctacac acgtactaca
atggcagtca tacagaggga agcaaaacag tgatgtggag 1260caaatcccta
aaagctgtcc cagttcagat tgcaggctgc aactcgcctg catgaagtcg
1320gaattgctag taatcgcgga tcagcatgcc gcggtgaata cgttcccggg
ccttgtacac 1380accgcccgtc acaccatgag agccggtaat acccgaagtc
cgtagcctaa ccgcaaggag 1440ggcgcggccg aaggtaggac tggtaattag
ggtgaagtcg taacaaggta gccgtatcgg 1500aaggtgcggc tggatcacct ccttt
1525231506DNAGordonibacter urolithinfaciensmisc_featureR=A or G,
Y=C or T 23acggagagtt tgatcctggc tcaggatgaa cgctggcggc gtgcctaaca
catgcaagtc 60gaacggttaa ggcgccttcg ggcgcgaata gagtggcgaa cgggtgagta
acacgtgacc 120aacctgcccc cctccccggg ataacgcgag gaaacccgcg
ctaataccgg atactccgcc 180cctcccgcat gggaggggcg ggaaagcccc
gacggagggg gatggggtcg cggcccatta 240ggtagacggc ggggcaacgg
cccaccgtgc ctgcgatggg tagccgggtt gagagaccga 300ccggccacat
tgggactgag atacggccca gactcctacg ggaggcagca gtggggaatt
360ttgcgcaatg gggggaaccc tgacgcagca acgccgcgtg cgggacgaag
gccttcgggt 420tgtaaaccgc tttcagcagg gaagaagttg acggtacctg
cagaagaagc cccggctaac 480tacgtgccag cagccgcggt aatacgtagg
gggcgagcgt tatccggatt cattgggcgt 540aaagcgcgcg taggcggccc
gtcaagcgga acctctaacc cgagggctca acccccggcc 600gggttccgaa
ctggcaggct cgagtttggt agaggaagat ggaattcccg gtgtagcggt
660ggaatgcgca gatatcggga agaacaccga tggcgaaggc agtcttctgg
gccatcaact 720gacgctgagg cgcgaaagct gggggagcga acaggattag
ataccctggt agtcccagcc 780gtaaacgatg ggygctaggt gtggggggat
catccctccg tgccgcagcc aacgcattaa 840gcrccccgcc tggggagtac
ggccgcaagg ctaaaactca aaggaattga cgggggcccg 900cacaagcagc
ggagcatgtg gcttaattcg aagcaacgcg aagaacctta ccagggcttg
960acatgctggt gaagccgggg aaacccggtg gccgagagga gccagcgcag
gtggtgcatg 1020gctgtcgtca gctcgtgtcg tgagatgttg ggttaagtcc
cgcaacgagc gcaacccctg 1080ccatatgttg ccagcattca gttggggact
catatgggac tgccggcgtc aagccggagg 1140aaggtgggga cgacgtcaag
tcatcatgcc ctttatgccc tgggctgcac acgtgctaca 1200atggccggta
caacgggccg cgacctggcg acaggaagcg aatccctcaa agccggcccc
1260agttcggatc ggaggctgca acccgcctcc gtgaagtcgg agttgctagt
aatcgcggat 1320cagcatgccg cggtgaatac gttcccgggc cttgtacaca
ccgcccgtca caccacccga 1380gtcgtctgca cccgaagccg ccggccgaac
ccgcaagggg cggaggcgtc gaaggtgtgg 1440agggtaaggg gggtgaagtc
gtaacaaggt agccgtaccg gaaggtgcgg ctggatcacc 1500tccttt
1506241535DNAFaecalitalea sp. 24atggagagtt tgatcctggc tcaggatgaa
cgctggcggc atgcctaata catgcaagtc 60gaacgaagtc tttaggaagc ttgcttccaa
agagacttag tggcgaacgg gtgagtaaca 120cgtaggtaac ctgcccatgt
gcccgggata actgctggaa acggtagcta aaaccggata 180ggtatgaggg
aggcatcttc ctcatattaa agcaccttcg ggtgtgaaca tggatggacc
240tgcggcgcat tagctggttg gtgaggtaac ggcccaccaa ggcgatgatg
cgtagccgac 300ctgagagggt gaacggccac attgggactg agacacggcc
caaactccta cgggaggcag 360cagtagggaa ttttcgtcaa tggggggaac
cctgaacgag caatgccgcg tgtgtgaaga 420aggtcttcgg atcgtaaagc
actgttgtaa gtgaagaatg ccatatagag gaaatgctat 480gtgggtgacg
gtagcttacc agaaagccac ggctaactac gtgccagcag ccgcggtaat
540acgtaggtgg caagcgttat ccggaatcat tgggcgtaaa gggtgcgtag
gtggcacgat 600aagtctgaag taaaaggcaa cagctcaact gttgtatgct
ttggaaactg tcgagctaga 660gtgcagaaga gggcgatgga attccatgtg
tagcggtaaa atgcgtagat atatggagga 720acaccagtgg cgaaggcggt
cgcctggtct gtaactgaca ctgatgcacg aaagcgtggg 780gagcaaatag
gattagatac cctagtagtc cacgccgtaa acgatgagaa ctaagtgttg
840gagagattca gtgctgcagt taacgcaata agttctccgc ctggggagta
tgcacgcaag 900tgtgaaactc aaaggaattg acgggggccc gcacaagcgg
tggagtatgt ggtttaattc 960gaagcaacgc gaagaacctt accaggcctt
gacatggata taaatgttct agagatagaa 1020agatagctat atatcacaca
ggtggtgcat ggttgtcgtc agctcgtgtc gtgagatgtt 1080gggttaagtc
ccgcaacgag cgcaaccctt gtcttctgtt accagcatta agttggggac
1140tcaggagaga ctgccggtga caaaccggag gaaggtgggg atgacgtcaa
atcatcatgc 1200cccttatggc ctgggctaca cacgtactac aatggcgcct
acaaagagca gcgacaccgc 1260gaggtggagc gaatctcata aagggcgtct
cagttcggat tgaagtctgc aactcgactt 1320catgaagtcg gaatcgctag
taatcgcaga tcagcatgct gcggtgaata cgttctcggg 1380ccttgtacac
accgcccgtc aaaccatggg agttggtaat acccgaagcc ggtggcataa
1440ccgcaaggag tgagccgtcg aaggtaggac cgatgactgg ggttaagtcg
taacaaggta 1500tccctacggg aacgtgggga tggatcacct ccttt
1535251530DNABlautia sp.misc_featureM=A or C, R=A or G, Y=C or T,
K=G or T, W=A or T 25tcagagagtt tgatcctggc tcaggatgaa cgctggcggc
gtgcttaaca catgcaagtc 60gagcgaagcr cttrarygga tctcttcgga ttgaaryttw
tktgactgag cggcggacgg 120gtgagtaacg cgtgggtaac ctgcctcata
cagggggata acagttagaa atggctgcta 180ataccgcata agcgcacagg
accgcatggt ctggtgtgaa aaactccggt ggtatgagat 240ggacccgcgt
ctgattagct agttggaggg gtaacggccc accaaggcga cgatcagtag
300ccggcctgag agggtgaacg gccacattgg gactgagaca cggcccagac
tcctacggga 360ggcagcagtg gggaatattg cacaatgggg gaaaccctga
tgcagcgacg ccgcgtgaag 420gaagaagtat ctcggtatgt aaacttctat
cagcagggaa gaaaatgacg gtacctgact 480aagaagcccc ggctaactac
gtgccagcag ccgcggtaat acgtaggggg caagcgttat 540ccggatttac
tgggtgtaaa gggagcgtag acggaagagc aagtctgatg tgaaaggctg
600gggcttaacc ccaggactgc attggaaact gtttttctag agtgccggag
aggtaagcgg 660aattcctagt gtagcggtga aatgcgtaga tattaggagg
aacaccagtg gcgaaggcgg 720cttactggac ggtaactgac gttgaggctc
gaaagcgtgg ggagcaaaca ggattagata 780ccctggtagt ccacgccgta
aacgatgaat actaggtgtc gggtggcaaa gccattcggt 840gccgcagcaa
acgcaataag tattccacct ggggagtacg ttcgcaagaa tgaaactcaa
900aggaattgac ggggacccgc acaagcggtg gagcatgtgg tttaattcga
agcaacgcga 960agaaccttac caagtcttga catccctctg accggcccgt
aacggggcct tcccttcggg 1020gcagaggaga caggtggtgc atggttgtcg
tcagctcgtg tcgtgagatg ttgggttaag 1080tcccgcaacg agcgcaaccc
ctatccttag tagccagcag gtrragctgg gcactctagg 1140gagactgccg
gggataaccc ggaggaaggc ggggacgacg tcaaatcatc atgcccctta
1200tgatttgggc tacacacgtg ctacaatggc gtaaacaaag ggaagcgaga
cagcgatgtt 1260gagcaaatcc caaaaataac gtcccagttc ggactgcagt
ctgcaactcg actgcacgaa 1320gctggaatcg ctagtaatcg cgaatcagaa
tgtcgcggtg aatacgttcc cgggtcttgt 1380acacaccgcc cgtcacacca
tgggagtcag taacgcccga agtcagtgac ccaaccttay 1440aggagggagc
tgccgaaggc gggaccgata actggggtga agtcgtaaca aggtagccgt
1500atcggaaggt gcggctggat cacctccttt 1530261528DNABarnesiella
intestinihominismisc_featureR=A or G, Y=C or T 26cgaagagttt
gatcctggct caggatgaac gctagcgaca ggcctaacac atgcaagtcg 60aggggcagcg
grgaggyagc aatacctttg ccggcgaccg gcgcacgggt gagtaacacg
120tatgcaatcc acctgtaaca gggggataac ccggagaaat ccggactaat
accccataat 180atgggcgctc cgcatggagr gtccattaaa gagagcaatt
ttggttacag acgagcatgc 240gctccattag ccagttggcg gggtaacggc
ccaccaaagc gacgatggat aggggttctg 300agaggaaggt cccccacatt
ggaactgaga cacggtccaa actcctacgg gaggcagcag 360tgaggaatat
tggtcaatgg tcggcagact gaaccagcca agtcgcgtga gggaagacgg
420ccctacgggt tgtaaacctc ttttgtcgga gagtaaagtr cgctacgtgt
agygtattgc 480aagtatccga agaaaaagca tcggctaact ccgtgccagc
agccgcggta atacggagga 540tgcgagcgtt atccggattt attgggttta
aagggtgcgt aggcggcacg ccaagtcagc 600ggtgaaattt ccgggctcaa
cccggactgt gccgttgaaa ctggcgagct agagtgcaca 660agaggcaggc
ggaatgcgtg gtgtagcggt gaaatgcata gatatcacgc agaaccccga
720ttgcgaaggc agcctgctag ggtgcgacag acgctgaggc acgaaagcgt
gggtatcgaa 780caggattaga taccctggta gtccacgcag taaacgatga
atactaactg tttgcgatac 840aatgtaagcg gtacagcgaa agcgttaagt
attccacctg gggagtacgc cggcaacggt 900gaaactcaaa ggaattgacg
ggggcccgca caagcggagg aacatgtggt ttaattcgat 960gatacgcgag
gaaccttacc cgggctcaaa cgcaggggga atgccggtga aagtcggcag
1020ctagcaatag tcacctgcga ggtgctgcat ggttgtcgtc agctcgtgcc
gtgaggtgtc 1080ggcttaagtg ccataacgag cgcaacccct atggacagtt
actaacgggt gaagccgagg 1140actctgtcta gactgccggc gcaagccgcg
aggaaggtgg ggatgacgtc aaatcagcac 1200ggcccttacg tccggggcga
cacacgtgtt acaatggcag gtacagaagg cagccagtca 1260gcaatgacgc
gcgaatcccg aaaacctgtc tcagttcgga ttggagtctg caacccgact
1320ccatgaagct ggattcgcta gtaatcgcgc atcagccatg gcgcggtgaa
tacgttcccg 1380ggccttgtac acaccgcccg tcaagccatg gaagccggga
gtacctgaag catgcaaccg 1440caaggagcgt acgaaggtaa taccggtaac
tggggctaag tcgtaacaag gtagccgtac 1500cggaaggtgc ggctggaaca cctccttt
1528271528DNABlautia sp.misc_featureM=A or C, R=A or G, Y=C or T,
K=G or T, S=G or C 27tcagagagtt tgatcctggc tcaggatgaa cgctggcggc
gtgcttaaca catgcaagtc 60gagcgaagca cttryyattg amtcttcgga rgatttrgca
tktgactgag cggcggacgg 120gtgagtaacg cgtgggtaac ctgcctcata
caggggaata acagttagaa atggctgcta 180atgccgcata agcgcacagg
rccgcatggt cyggtgtgaa aaactsmggt ggtatgagat 240ggrcccgcgt
ctgattaggt agttggcggg gtaacggccc accaagccga cgatcagtag
300ccgacctgag agggtgaccg gccacattgg gactgagaca cggcccagac
tcctacggga 360ggcagcagtg gggaatattg cacaatggag gaaactctga
tgcagcgacg ccgcgtgaag 420gaagaagtat ctcggtatgt aaacttctat
cagcagggaa gaaaatgacg gtacctgact 480aagaagcccc ggctaactac
gtgccagcag ccgcggtaat acgtaggggg caagcgttat 540ccggatttac
tgggtgtaaa gggagcgtag acggacgggc aagtctgatg tgaaagcccg
600gggcttaacc ccgggactgc attggaaact gtccatcttg agtgccggag
aggtaagcgg 660aattcctagt gtagcggtga aatgcgtaga tattaggagg
aacaccagtg gcgaaggcgg 720cttactggac ggtaactgac gttgaggctc
gaaagcgtgg ggagcaaaca ggattagata 780ccctggtagt ccacgccgta
aacgatgaat actaggtgtc gggttgcaaa gcaatccggt 840gccgcagcaa
acgcagtaag tattccacct ggggagtacg ttcgcaagaa tgaaactcaa
900aggaattgac ggggacccgc acaagcggtg gagcatgtgg tttaattcga
agcaacgcga 960agaaccttac caagtcttga catctgcctg accgttcctt
aaccggaact ttccttcggg 1020acaggcaaga caggtggtgc atggttgtcg
tcagctcgtg tcgtgagatg ttgggttaag 1080tcccgcaacg agcgcaaccc
ctgtccttag tagccagcag tccggctggg cactctaggg 1140agactgccgg
ggataacccg gaggaaggcg gggacgacgt caaatcatca tgccccttat
1200gatttgggct acacacgtgc tacaatggcg taaacaaagg gaagcggagt
ggtgacactg 1260agcaaatctc aaaaataacg tcccagttcg gactgcagtc
tgcaactcga ctgcacgaag 1320ctggaatcgc tagtaatcgc gaatcagaat
gtcgcggtga atacgttccc gggtcttgta 1380cacaccgccc gtcacaccat
gggagtcagt aacgcccgaa gtcagtgacc taaccgcaag 1440ggaggagctg
ccgaaggcgg gaccgataac tggggtgaag tcgtaacaag gtagccgtat
1500cggaaggtgc ggctggatca cctccttt 1528281530DNALachnospira
sp.misc_featureM=A or C, R=A or G, Y=C or T, W=A or T 28ttatgagagt
ttgatcctgg ctcaggatga acgctggcgg cgtgcttaac acatgcaagt 60cgaacgaagc
atttgmgacr gattyyttcg grwtgaagac ttttatgact gagtggcgga
120cgggtgagta acgcgtgggt aacctgcctc acacaggggg atagcagttg
gaaacggctg 180ataataccgc ataagcgcac agtaccgcat ggtacagtgt
gaaaaactcc ggtggtgtga 240gatggacccg cgtctgatta gcttgttggc
rgggtaacgg ccyaccaagg caacgatcag 300tagccgacct gagagggtga
ccggccacat tgggactgag acacggccca gactcctacg 360ggaggcagca
gtggggaata ttgcacaatg gaggaaactc tgatgcagcg acgccgcgtg
420agtgaagaag taattcgtta tgtaaagctc tatcagcagg gaagatagtg
acggtacctg 480actaagaagc tccggctaaa tacgtgccag cagccgcggt
aatacgtatg gagcaagcgt 540tatccggatt tactgggtgt aaagggagtg
taggtggcat cacaagtcag aagtgaaagc 600ccggggctca accccgggac
tgcttttgaa actgtggagc tggagtgcag gagaggcaag 660tggaattcct
agtgtagcgg tgaaatgcgt agatattagg aggaacacca gtggcgaagg
720cggcttgctg gactgtaact gacactgagg ctcgaaagcg tggggagcaa
acaggattag 780ataccctggt agtccacgcc gtaaacgatg aatactaggt
gtcggggctc ataagagctt 840cggtgccgca gcaaacgcaa taagtattcc
acctggggag tacgttcgca agaatgaaac 900tcaaaggaat tgacggggac
ccgcacaagc ggtggagcat gtggtttaat tcgaagcaac 960gcgaagaacc
ttaccaagtc ttgacatcct cttgrccggt cagtaatgtg rycttttctt
1020cggaacaaga gtgacaggtg gtgcatggtt gtcgtcagct cgtgtcgtga
gatgttgggt 1080taagtcccgc aacgagcgca acccctattc ttagtagcca
gcatttaagr tgggcactct 1140aggaagactg ccagggataa cctggaggaa
ggtggggatg acgtcaaatc atcatgcccc 1200ttatgacttg ggctacacac
gtgctacaat ggcgtaaaca aagtgaagcg agagtgtgag 1260cttaagcaaa
tcacaaaaat aacgtctcag ttcggattgt agtctgcaac tcgactacat
1320gaagctggaa tcgctagtaa tcgcgaatca gaatgtcgcg gtgaatacgt
tcccgggtct 1380tgtacacacc gcccgtcaca ccatgggagt cggaaatgcc
cgaagtcggt gacctaacga 1440aagaaggagc cgccgaaggc aggtctgata
actggggtga agtcgtaaca aggtagccgt 1500atcggaaggt gcggctggat
cacctccttt 1530291530DNARoseburia faecismisc_featureR=A or G, Y=C
or T, S=G or C 29atgagagttt gatcctggct caggatgaac gctggcggcg
tgcttaacac atgcaagtcg 60aacgaagcac tctatttgat tttcttcggr aatgaagatt
ttgtgactga gtggcggacg 120ggtgagtaac gcgtgggtaa cctgcctcat
acagggggat aacagttgga aacgactgct 180aataccgcat aagcgcacag
gatygcatgr tccggtgtga aaaactccgg tggtatgrga 240tggacccgcg
tctgattagc cagttggcag ggtaacggcc taccaaagcg acgatcagta
300gccgacctga gagggtgacc ggccacattg ggactgagac acggcccaaa
ctcctacggg 360aggcagcagt ggggaatatt gcacaatggg ggaaaccctg
atgcagcgac gccgcgtgag 420cgaagaagta tttcggtatg taaagctcta
tcagcaggga agaagaatga cggtacctga 480ctaagaagca ccggctaaat
acgtgccagc agccgcggta atacgtatgg tgcaagcgtt 540atccggattt
actgggtgta aagggagcgc aggcggtgcg gcaagtctga tgtgaaagcc
600cggggctcaa ccccggtact gcattggaaa ctgtcgtact agagtgtcgg
aggggtaagt 660ggaattccta gtgtagcggt gaaatgcgta gatattagga
ggaacaccag tggcgaaggc 720ggcttactgg acgataactg acgctgaggc
tcgaaagcgt ggggagcaaa caggattaga 780taccctggta gtccacgccg
taaacgatga atactaggtg tcggggagca ttgctcttcg 840gtgccgcagc
aaacgcaata agtattccac ctggggagta cgttcgcaag aatgaaactc
900aaaggaattg acggggaccc gcacaagcgg tggagcatgt ggtttaattc
gaagcaacgc 960gaagaacctt accaagtctt gacatcccga tgacagagta
tgtaatgtas yytcycttcg 1020grgcatcggt gacaggtggt gcatggttgt
cgtcagctcg tgtcgtgaga tgttgggtta 1080agtcccgcaa cgagcgcaac
ccctgtyctt agtagccagc ggttcggccg ggcactctag 1140ggagactgcc
agggataacc tggaggaagg cggggatgac gtcaaatcat catgcccctt
1200atgacttggg ctacacacgt gctacaatgg cgtaaacaaa gggaagcrra
gccgtgaggc 1260cgagcaaatc tcaaaaataa cgtctcagtt cggactgtag
tctgcaaccc gactacacga 1320agctggaatc gctagtaatc gcagatcaga
atgctgcggt gaatacgttc ccgggtcttg 1380tacacaccgc ccgtcacacc
atgggagttg gaaatgcccg aagtcagtga cccaaccgca 1440aggagggagc
tgccgaaggc aggttcgata actggggtga agtcgtaaca aggtagccgt
1500atcggaaggt gcggctggat cacctccttt 15303020DNAArtificial
Sequenceprimer sequencemisc_featureM=A or C 30agagtttgat ymtggctcag
203121DNAArtificial Sequenceprimer sequence 31acggytacct tgttacgact
t 21
* * * * *
References